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1 Module I
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INTRODUCTION TO MARKETING
RESEARCH - I
Unit Structure
1.0 Objective
1.1 Introduction
1.2 Marketing Research
1.3 Steps in Marketing Research
1.4 Summary
1.5 Exercise
1.6 References
1.0 OBJECTIVE
After studying this unit, the students will be able to:
Understand the concept of marketing research and its features,
function and importance.
Get an insight into the steps in marketing research and various ethical
practice in the field of marketing research.
1.1 INTRODUCTION
Good instincts and intuition certainly play important roles in business.
But, gut feelings about customers’ needs and preferences aren’t enough. If
business want to minimize risk and improve chances of success, business
need sound and objective data. That’s where market research comes in.
Market research is the process of collecting and analysing information
about the customers business want to reach, calledtarget market. This
information providesbusiness intelligence that helps in making informed
decisions. Market research can help in creating a business plan, launch a
new product or service, improve existing products and services, expand
into new markets, develop an advertising campaign, set prices, andselect a
business location.
1.2 MARKETING RESEARCH
The environment for marketing ha s become extremely dynamic. Without
adequate preparation, it is difficult for organizations to survive in such an munotes.in
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2 environment. Marketing research is one of the most effective tools that
help organizations excel in the marketplace. Obtaining necessary
infor mation about customers’ tastes and preferences is the key to business
success.
Marketing research provides information about consumers and their
reactions to various products, prices, distribution, and promotion
strategies. Marketers who collect accurate a nd relevant information
quickly and design their strategies quicker than their competitors are more
likely to be successful.
Marketing research helps in effective planning and implementation of
business decisions by providing accurate, relevant, and timely
information. The process of marketing research involves a series of steps
that systematically investigate a problem or an opportunity facing the
organization.
The research process provides a scientific platform, contrary to the
traditional intuitive appro ach of decision making by managers which used
to put large amounts of resources of the organization at risk. Organizations
in areas such as IT, pharmaceuticals, telecom, manufacturing,
transportation, advertising, banking, law, education and even governmen ts
utilize marketing research to find solutions to different kinds of decision -
making problems.
1.2.1 Definition
According to Philip Kotler, Marketing research is defined as, “the
systematic design, collection, analysis, and reporting of data and findings
relevant to a specific marketing situation facing the company”
“Marketing research is the inclusive term which embraces all research
activities carried on for the management of marketing work, the gathering,
recording and analysing of all facts about probl ems relating to the
transfer and sale of goods and services from producer to
consumer.” Harry Hapner
“The systematic gathering, recording and analysis of data about problems
relating to the marketing of goods and services” The American
Marketing Association.
“The systematic objective and exhaustive research for and study of the
facts relevant to any problem in the field of marketing.” RichardCrisp
“Marketing research is the careful and objective study of product design,
markets, and such transfer activities as physical distribution and
warehousing, advertising and sales management.” Clark and Clark
Thus, Marketing research is the systematic gathering, recording, and
analysis of qualitative and quantitative data about issues relating
to marketing products and services.
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3 Marketing Research V/s Market Research
Marketing research is a broader term including market research.
Marketing research is concerned with all the major functions of marketing.
Market research is primarily concerned with knowing the capacity of the
market to absorb a particular product. Marketing research is not only
concerned with the jurisdiction of the market but also covers nature of the
market, product analysis, sales analysis, time, place and media of
advertising, personal selling and marketing intermediaries and their
relationships etc.
1.2.2 Features of Marketing Research
1. Part of Marketing Management: Marketing research is one of the
important part and function of marketing management. The information
collected through marketing research helps marketing depar tment in
framing appropriate marketing mix. It also helps marketing managers to
keep updated with latest information, trends and changes in marketing
environment which in turn facilitates them in decision making.
2. Systematic Study: Marketing research is sy stematic study related
various aspects of marketing. It follows well defined procedures for
collection and analysis of marketing related data. Some of the steps of
marketing research are as follows:
Collection of data
Recording of data
Tabulating of data
Analysis and Interpretation of data
Each of these steps is performed by experts under the supervision of
marketing department. Hence, marketing research is systematic study from
beginning till end.
3. Market Oriented: Marketing research is market -oriented ac tivity. It
starts with marketing problem and ends with solution of said marketing
problem. It helps the firm in identifying needs and wants of customers and
also provides profitable ways to satisfy that needs and wants. It also
facilitates marketing depart ment in establishing channel of distribution so
that products can reach market easily, quickly and cheaply.
4. Continuous Process: Marketing environment is dynamic in nature.
The constant changes in takes place in marketing environment. It is
imperative for marketing managers to keep abreast with latest change
related to customer needs and preferences, competitors, suppliers, dealers
etc. Hence, firms need to undertake process of marketing research on
continuous basis.
5. Data Collection: Marketing research gi ves importance to accurate
data collection. In marketing research, suitable data should be collected
objectively and accurately. The data collected must be reliable. It should munotes.in
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4 be analysed in a systematic manner. This will provide comprehensive
picture of t he marketing situation and possible solutions.
6. Larger Scope: The scope of marketing research is wider and larger.
It is specialized activity which includes several functions like:
Product research
Market research
Consumer research
Promotion research
Price research
Distribution research
7. Helps in Decision Making: Marketing research assist managers in
decision making process. It helps managers in taking practical and sound
decisions. The information collected through marketing research helps
marketing manage rs in:
Product design decisions
Pricing decisions
Promotion decisions
Place decisions
It not only helps marketing managers but also other functional department
managers like finance, human resource, production etc. in decision
making. The decisions based on experience and research is better than
decision based on intuition.
8. Applied Research: Marketing research is branch of applied
research. It is applied knowledge. It is concerned with specific marketing
problem and suggests alternative solutions and poss ible outcome of each
alternative. The research is conducted to understand specific marketing
problems.
9. Intelligence Tool: In recent time, data and information is considered
important part of marketing. It is said that those possess accurate
marketing da ta, can control the market and business. Marketing research
acts as intelligence tool of management. It is type of commercial
intelligence activity. It gives management first -hand information related to
various aspects of markets which provides competitive advantage to firm.
10. Use of Different Methods: Marketing department used different
methods for undertaking marketing research. The mathematical and
statistical tools are used for data analysis and interpretation. Percentages,
ratios, averages, z -test, t -test, chi -square tests, etc. are used for
presentation and interpretation of findings. The use of computer software
has made it more convenient for in -depth analysis, cross -sectional studies,
detection of errors in sampling and questionnaires.
The use of ma rketing research methods depends upon the nature,
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5 the method which is suitable for the conduct of marketing research project.
This selection is important as the quality of research w ork depends on the
method used for the marketing research purpose.
11. Not Pure Science: Although, marketing research conducted with
helps of systematic process and scientific methods are adopted during
different stages of marketing research but marketing res earch is not pure
and exact science. It only suggests possible solutions to marketing
manager for consideration and selection.
12. Uncertain in Nature: Marketing research is uncertain in nature.
The main focal point for any marketing research is consumers. It studies
consumers behaviour but it is difficult to predict consumers behaviour
precisely and accurately. It is not a physical science, but social science.
Due to this inherent nature, it suffers from certain levels of inaccuracy.
1.2.3 Functions of Market ing Research
Marketing research performs five basic functions. These areDescription,
Evaluation, Explanation, Prediction and finally Aid in Decision -Making.
These functions are related to the research project undertaken. Usually,
every research study perfo rms all the five functions explained below:
1. Description: Marketing research provides data and gives
information or description of customers who buy the product. This
includes information about their age, sex, education, income and the
amount of money that they are willing to spend on the product.
Description of the customers is useful in order to draw certain conclusions
about the customers and their buying behaviour. Even marketing strategies
can be decided as per the information available.
2. Evaluation: Marketing research is useful for understanding the
views or reactions of the buyers. This includes views of consumers on
packaging, advertising, sales promotion measures used. A manufacturer
gets these details as well as the information about his product in
comparison with the products of his competitors. This facilitates
evaluation of the marketing policies. For example, how farthepackaging of
the product is attractive to consumers or superior as compared to
packaging by competitors and so on.
3. Explanation: Marketing research givesexplanation to certain
questions of a manufacturer. It may be related to decline in sales, retailers’
negative reaction or resistance of consumers in a particular marketing
area. Marketing research enables a manufacturer to understa nd why sales
are reducingor why the response of the retailers is negative or why
consumers in a particular region are not willing to purchase a specific
product. Such explanation is important as it enables a manufacturer to
adjust his marketing policies in order to rectify the prevailing
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6 4. Prediction: Marketing research conducts prediction function. Such
predictions may be related to consumers, market environment, market
competition, possible socio -economic changes and so on.
This pr ediction function enables a manufacturer to understand how much
people will spend on the specific product in the next year or the fashions
that consumers may prefer in the next year. In addition, prediction about
the possible turnover in the years to come is also possible through suitable
marketing research studies.
In brief, marketing research is useful for understanding the marketing
environment likely to develop in future. This facilitates proper adjustment
in the marketing policies for the future peri od. In this sense, the prediction
function is important even when all predictions made through research
studies may not prove to be fully correct. However, the trend indicated can
be used for appropriate policy decisions.
5. Helps in Decision Making: One mor e function of marketing
research is to facilitate the process of decision -making in the marketing
field. Marketing research guides the manufacturer as regards the manner
in which he can make effective advertising appeal or create incentive
among his salesm en or distributors. It also gives him guidance as regards
price fixation and sales promotion techniques that will be useful for the
future period. This function of marketing research is closely related to
other functions that it performs. These functions f acilitate reasonably
correct decision -making by marketing managers.
In brief, the basic function of marketing research is to support marketing
decision -making process. Marketing research does not provide ready -
made decisions or exact solutions on all marke ting problems. It only
provides the clues or possible solutions that should be taken into
consideration in the decision -making process. It provides support to skills
and abilities of marketing managers.
1.2.4 Significance of Marketing Research in Marketing Decision
Making:
1. Identifying Needs and Wants: Marketing and market is all about
customers. It is very crucial for the firm to understand their target market
and target customers. Marketing research helps in identifying consumers
needs and wants. It also f acilitates mangers to analyse their potential
customers from various aspects like age, gender, income, standard of
living etc.
2. Formulating Marketing Strategies: Today, market has become
more competitive. It is not only restricted to local market but beco me
national and also global market. Marketing research facilitated marketing
managers in formulating marketing strategies for local, national and global
market.
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7 3. Framing Promotion Mix: Promotion mix plays crucial role in
product life cycle. Marketing rese arch uses promotional research to study
media mix, adver tising effectiveness and integrated communication tools.
Research on such aspects will help in promoting effectively a company’s
product in the market.
4. Assist Selling Process: Marketing research ass ist in selling process
of the product. It is used to analyse and evaluate performances of a
company within a particular market. It also studies effectiveness of a sales
force. It helps in identify ing sales territories. Such information helps the
companies in identifying areas of shortcoming in sales. It also examines
alternative methods for distribution of goods.
5. Helps in Sales Forecasting: The most challenging task for any
production manager is to keep optimum levels of inventory. However,
production is undertaken in anticipation of demand. Therefore, scientific
forecast of sales is required. Marketing research helps in sales forecasting
by using market share method, sales force estimate method and jury
method. This can also help in fixing sales quotas an d marketing plans.
6. Revitalize Brands: Marketing research is used to study and find out
the existing brand position. It finds out the recall value of brands. It
explores the possibilities of brand extension or prospects of changing
existing brand names. Th e main purpose of marketing is to create brand
loyalty. Marketing research helps in developing techniques to popularize
and retain brand loyalty.
7. Introduction of New Products: Marketing research helps in testing
the new products in one or two markets on a small scale. This helps in
finding out consumer response to new product and develop a suitable
marketing mix. It reveals the problems of the customers regarding new
products. Thus, it controls the risk involved in introducing a new product.
8. Export Promot ions: The development in transport and
communication has helped in globalization and digitalization of world
trade. This has helped in boosting the growth of international markets.
Marketing research helps in conducting market survey for export. It.
collec ts information on marketing environ ment prevailing in a country. By
collecting data on consumers from different countries, it indicates export
potentials.
9. Assist in Decision Making: Marketing research plays a vital role in
the decision -making processes b y supplying relevant, up -to-date and
accurate data to the decision -makers. Managers need up -to-date
information to access customer needs and wants, market situation,
technological change and extent of competition.
10. Identify Business Opportunities: Marketin g research helps in
identifying business opportunities. It helps in identifying new market
opportunities for existing and new products. For instance, various munotes.in
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8 marketing research point out growing trend of binge watching which in
turn created new trend of en tertainment called OTT platforms i.e., web
series.
11. Lower Business Risks: Marketing research helps in lowering the
various risks associated with business. It provides information on market
share, nature of competition, customer satisfaction levels, sales
performances and channel of distribution etc. This helps the firms in
solving problems and thus it will reduce the business risks.
12. Provides Direction: Marketing works on the bases of a lot of
marketing research data derived from the research work, analys es,
marketing research projects, etc. It does not work on simply pushing its
product on a customer, unlike sales. Marketing researchers can guide the
requirement of the consumer and what is really important for him.
Marketing research can direct firm for b oth short -term as well as long -
term requirement of focused customer.
13. Creates Future Customers: Unlike sales, marketing research does
not focus on selling only today for achieving target of the day or target of
the month; it focuses on creating a customer base for today as well as
tomorrow. The base is created by creating a relationship with the customer
by knowing his likes and dislikes, by being in touch with the king of the
market on regular basis in some form or the other.
1.2.5 Limitations of Marketing Research:
Marketing research plays a crucial role in excelling marketing
performance. In fact, it is inevitable to understand and treat customers
more effectively than competitors. Marketer can satisfy customers by
maintaining close contact with the targe t market by marketing research. It
is one of the basic tasks of modern marketing. However, it is not free from
limitations. Marketing manager must be aware of these limitations.
1. Extraneous Factors: Extraneous means external and uncontrollable
factors. In m ost of the cases, the extraneous factors affect marketing
research results adversely. Due to impact of such factors, the net impact
cannot be estimated.
For example, if marketer wants to study the impact of 10% price rise on
demand and he raises price by 10%. As a result, demand falls by 20%.
Here, decrease in demand cannot be fully attributed to price hike only.
Demand might have been affected by other factors like introduction of
new superior product, attractive offer of competitors, availability of
powe rful substitutes, etc., over and above price rise.
Whatever degree of precaution is taken, one cannot eliminate effect of
such factors completely, and as a result, marketing research cannot serve
the purpose.
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9 2. Time Gap: The time gap makes marketing resea rch irrelevant.
Systematic marketing research project needs more time. It takes weeks,
months, even years. When marketing research is carried on to investigate
or solve the problem, final outcomes are available after considerable time.
When outcomes are ma de available, situations might have been changed
thoroughly or problem for which research was made might have been
solved automatically. Decision -maker needs information in time. But
practically, it is not possible. Sometimes, time, money, and efforts
contribute nothing.
3. High Cost: To conduct marketing research systematically is a
luxury. A firm needs money for research design, data collection, data
analysis, interpretation, and report preparation. Statisticians and computer
experts charge heavy fees. When research is conducted regularly, a
company has to maintain a separate well -equipped marketing research
department. Marketing research has become costlier. So, it is difficult for
medium and small companies to afford.
4. Dynamic Changes: Today’s market is ch aracterized by tremendous
changes. Whatever is applicable or relevant today is out -dated tomorrow.
Due to rapid changes, marketing research cannot serve the purpose.
Research results or outcomes available after the specific time period seem
irrelevant or m eaningless.
5. Problem of Trust and Accuracy: Marketing research is based on
trust and accuracy. Right from the identification of problem to the final
outcomes, all depends on trust. Company has to trust on marketing
research officer; research officer has to trust on field officer; and field
officer has to rely on response of respondents. At any stage of marketing
research, accuracy is vital issue. To the extent inaccuracy prevails,
marketing research results suffer.
6. Biased in Nature: When human being is inv olved, a completely
bias-free response or result is not possible. Effect of personal value,
prejudice, attitudes, needs, and other socio -cultural factors affect the
objectivity of research adversely. Subjectivity may lead to utter chaos.
7. Inherent Risks: In every economic decision, there exists risk and
uncertainly. Marketing research cannot eliminate risk and uncertainty. It is
an attempt to minimize degree of risk. So, heavy costs on marketing
research don’t guarantee safety and certainty.
8. Applicability: Contribution of research project depends not only on
quality and reliability alone, but also the proper use of information. Many
times, marketing research reports remain just a formality for top
management. Recommendations are neither considered seriously nor
implemented fully.
9. Differences of Opinions: Marketing research activity involves a
number of people such as marketing manager, field officer, data analysts, munotes.in
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10 and finally decision -maker. All these people have different objectives,
backgrounds, and pers pectives. Consistency or parity among them is a
vital issue. Unless high degree of integration and intimacy among them
exit, one cannot expect a success. In fact, it is difficult.
10. Not Problem Solver: It is interesting and shocking to state that
marketing research does not solve any problem directly. It is not a
problem -solving technique but can assist to solve it. It is not a magic stick
to solve marketing problems; it is a source of information. To the extent
source is reliable and is used properly, it is useful. Even, an excellent
research project is useless if outcomes are not considered.
11. Limited Scope: Marketing research solves many business -related
problems. However, it cannot solve all business problems. It cannot solve
problems related to consumer b ehaviour, income and expenditure
relationship, etc. Thus, its scope is limited.
12. Limited Practical Value: Marketing research is only an academic
exercise. It is mainly based on a hypothetical approach. It gives theoretical
solutions. It does not give reali stic solutions to real -life problems. Its
solutions look good on paper but are harder to implement in a real sense.
Thus, it has a limited practical value.
Marketing manager and those involved in marketing research activity
must be aware of these limitatio ns or practical problems. Note that these
limiting factors cannot be completely eradicated. Attempts should be made
to minimize adverse impact of these limiting factors. Careful plan,
adequate budget, teamwork, accuracy, timeliness, proper use and
implemen tation, etc., have a strong prospect to contribute in successful
marketing research.
1.3 STEPS IN MARKETING RESEARCH
Marketing research exercise may take many forms but systematic enquiry
is a feature common to all such forms. Being a systematic enquiry, i t
requires a careful planning of the orderly investigation process. Though it
is not necessary that all research processes would invariably follow a
given sequence, yet marketing research often follows a generalised pattern
which can be broken down and stu died as sequential stages.
1. Identifying and Defining Problem: The market research process
begins with the identification “of a problem faced by the company. The
clear -cut statement of problem may not be possible at the very outset of
research process becaus e often only the symptoms of the problems are
apparent at that stage. Then, after some explanatory research, clear
definition of the problem is of crucial importance in marketing research
because such research is a costly process involving time, energy and
money. Clear definition of the problem helps the researcher in all
subsequent research efforts including setting of proper research objectives,
the determination of the techniques to be used, and the extent of
information to be collected. munotes.in
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11
It may be noted that the methods of explanatory research popularly in use
aresurvey of secondary data, experience survey, or pilot studies, i.e.,
studies of a small initial sample. All this is also known as ‘preliminary
investigation’.
2. Statement of Research Objectives: After identifying and defining
the problem with or without explanatory research, the researcher must take
a formal statement of research objectives. Such objectives may be stated in
qualitative or quantitative terms and expressed as research questions,
statement or hypothesis. For example, the research objective, “To find out
the extent to which sales promotion schemes affected the sales volume” is
a research objective expressed as a statement.
On the other hand, a hypothesis is a statement that can be ref uted or
supported by empirical finding. The same research objective could be
stated as, “To test the proposition that sales are positively affected by the
sales promotion schemes undertaken this winter.”
Example of another hypothesis may be: “The new pack aging pattern has
resulted in increase in sales and profits.” Once the objectives or the
hypotheses are developed, the researcher is ready to choose the research
design.
3. Preparation of Research Design: After defining the research
problem and deciding the objectives, the research design must be
developed. A research design is a master plan specifying the procedure for
collecting and analysing the needed information. It represents a framework
for the research plan of action.
The objectives of the study are included in the research design to ensure
that data collected are relevant to the objectives. At this stage, the
researcher should also determine the type of sources of information
needed, the data collection method (e.g., survey or interview), the
samplin g, methodology, and the timing and possible costs of research.
4. Planning for Sample: Sampling involves procedures that use a
small number of items or parts of the ‘population’ (total items) to make
conclusion regarding the ‘population’. Important questions in this regard
who are to be sampled as a rightly representative lot? Which is the target
‘population’? What should be the sample size how large or how small?
How to select the various units to make up the sample?
5. Data Collection: The collection of data relates to the gathering of
facts to be used in solving the problem. Hence, methods of market
research are essentially methods of data collection. Data can be secondary,
i.e., collected from concerned reports, magazines and other periodicals,
especially wr itten articles, government publications, company
publications, books, etc.
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12 Data can be primary, i.e., collected from the original base through
empirical research by means of various tools.
There can be broadly two types of sources
a. Internal sources: exist ing within the firm itself, such as accounting data,
salesmen’s reports, etc.
b. External sources: outside the firm.
6. Processing and Analysis of Data: Once data have been collected,
these have to be converted into a format that will suggest answers to the
initially identified and defined problem. Data processing begins with the
editing of data and its coding. Editing involves inspecting the data -
collection forms for omission, legibility, and consistency in classification.
Before tabulation, responses need to be classified into meaningful
categories.
The rules for categorizing, recording and transferring the data to ‘data
storage media’ are called codes. This coding process facilitates the manual
or computer tabulation. If computer analysis is being used, the data can be
key punched and verified.
Analysis of data represents the application of logic to the understanding of
data collected about the subject. In its simplest form analysis may involve
determination of consistent patterns and summarising of appropri ate
details.
The appropriate analytical techniques chosen would depend upon
informational requirements of the problem, characteristics of the research
designs and the nature of the data gathered. The statistical analysis may
range from simple immediate an alysis to very complex multivariate
analysis.
7. Formulating Conclusion: The final stage in the marketing research
process is that of interpreting the information and drawing conclusion for
use in managerial decision. The research report should clearly and
effectively communicate the research findings and need not include
complicated statement about the technical aspect of the study and research
methods.
Often the management is not interested in details of research design and
statistical analysis, but instea d, in the concrete findings of the research. If
need be, the researcher may bring out his appropriate recommendations or
suggestions in the matter. Researchers must make the presentation
technically accurate, understandable and useful.
1.3.1 Ethics in Mark eting Research
A basic role for a marketing researcher is that of intermediary between the
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13 facilitates the flow of information from the market or customer to the
producer of the good or se rvice.
Such a situation, with three major players the producer, the customer and
the market researcher often set the stage for conflicts of interest which can
give rise to ethical problems. Given the inevitability of ethical dilemmas in
marketing research, well -established ethical guidelines are critical.
For example, Council of American Survey Research Organizations
(CASRO) has outlined some of the important dos and don’ts of ethical
research:
DO respect the rights of all research participants: confidentia lity,
transparency, and privacy. Ensure that all participants are voluntary,
and that they have the right to withdraw their consent at any point
during the research process. Respondents must also be informed if they
are being filmed or recorded.
DO be sur e to cite the name of the firm that conducted the research, the
purpose, and the dates of the study in any reports.
DON’T cite any research in which the responses have been influenced
or coerced.
DON’T ask the researchers for confidential information a bout the
respondents or their responses.
DON’T dictate the methods used by the firm hired to conduct the
research.
DON’T ask for quantitative analytics from a qualitative study, and vice
versa.
Marketing ethics is the area of applied ethics which deals with the moral
principles behind the operation and regulation of marketing.
Ethics in Marketing research refers to moral principles or values that a
researcher or research organization should consider.
1. Privacy: Privacy is a major concern for customers tod ay, especially
after the many scandals of companies misusing customer information.
Informed consent and anonymity & confidentiality are three important
elements involved in the right to privacy.
With companies having an unprecedented ability to collect an d store
massive amounts of customer data, the importance of ethics in marketing
research has never been higher. The company must ensure privacy of the
respondents.
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14 2. Rights and Obligations: Everyone involved in the market research
process, from clients and researchers to the public and respondents, has
rights and obligations they expect to be met.
Paying attention to the ethical importance of meeting the rights and
obligations of everyone involved is the best way to avoid any unethical
concerns when it come s to market research methods.
3. Confidentiality: The researcher must ensure protection of data or
confidentiality of data by following ways:
Researcher or research organization should protect data properly.
They should keep confidential data or information very safe and
secure.
Any client or outside person should not access confidential and
important data from the organization.
4. Deceptive Practice: The importance of ethics in marketing research
doesn’t just apply to the way participants are treated but mark et research
methods as well. Companies today have more access to customer data than
ever before and this amount of access can easily lead to deceptive
practices.
Practices, like misrepresenting research results and not disclosing to
consumers that their data is being collected etc. are some of the deceptive
practices in marketing research. Lying and deceiving customers to access
and gather information is ethically wrong and could backfire in a
devastating way.
5. Use of Data: Information or data collected from respondents should
not be used for any other purpose or for any other research work. In this
case, the researcher plays a crucial role and he can assure respondents
about the security of the opinions and information given by the
respondent.
6. Compulsion to Respond: The researcher should not force any
respondent for answers. The researcher can explain the importance or
necessity of answer to that question for research work, but he/she should
not make compulsion or impel respondents to answer a particular
question.
7. Personal Questions: In case of personal or sensitive questions, the
researcher should give time to respondents to think about i t, and refuse to
participate in the study.
Researcher or trained staff of appropriate sex can be used to reduce
embarrassment caused. For example, suppose questions are related to the
female product, then it will be better to select female staff to do the
research.
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15 8. Incomplete Reporting: The researcher should not prepare
incomplete report. The incomplete report includes:
May not disclosing potentially damaging information about the product
Leaving uninformed about undesirable features or characteristics o f the
product
May hide or omit negative information or may avoid reporting
situational details that are necessary
9. Confirmation Bias: Confirmation bias is the tendency to search for
or favour information that is consistent and confirms one’s existing
belie fs. It is one of the most prevalent and long -recognized forms of bias
present in market research. Failing to interpret information in an unbiased
way can lead to misjudgements and inaccurate analysis. This results in a
biased favoring, interpretation, and recall of information.
To combat confirmation bias, researchers must consider alternative
hypotheses and avoid forming a hypothesis too early.
10. Culture Bias: Culture bias is the interpretation of situations, actions,
or data based on the standards of one 's own culture. This bias can also
potentially lead to stigma and stereotyping based on assumptions. Thus, it
is important to avoid generalizations when examining data.
Overall, it is difficult to conduct market research without bias. However,
through un derstanding its potential threats, analysts can provide insightful,
unbiased information to the client .
11. Big Data and Privacy: The term “big data” refers to data that is
continuing to come at a higher velocity, volume, and variety than ever
before. It is a lso more complex than traditional data. Sources of big data
are also becoming more complex.
Big data is now being pulled from mobile devices, social media, and
numerous other sources. Big data makes use of advanced technologies
such as location -based tec hnology, facial recognition, and autonomous
sensors. This means large amounts of data are being collected
independently of human action.
This allows market researchers to gather a wide variety of information to
gain valuable insights. This data allows co mpanies to access even more
data while the consumer may have little or no awareness. However, using
big data has also raised concerns regarding individual privacy and its
implications.
1.4 SUMMARY
Marketing research is usually the first step in the market ing process, after
ideas for products are conceived. Small companies conduct marketing
research to obtain information from the marketplace. They use it to solve munotes.in
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16 problems, obtain information on competitors and determine the needs and
wants of non -paying con sumers and customers. Marketers then analyse the
data and develop various marketing strategies. It’s marketing’s job to
leverage research to reach the best possible solution based on the research
available. Then, they must implement the solution, modify th e solution,
and successfully deliver that solution to the market.
Marketing research often focuses on understanding:
The customer (purchasers, consumers, influencers)
The company (product design, promotion, pricing, placement, service,
sales)
The competito rs (and how their market offerings interact in the market
environment)
Many types of marketing research studies can assist with this
“Company -Customer -Competition” scope, such as:
Monitoring customers and markets
Measuring awareness, attitudes, and image
Tracking product usage behaviour
Diagnosing immediate business problems
Supporting strategy development
Marketing research serves marketing management by providing
information which is relevant to decision making. Marketing research does
not itself make th e decisions, nor does it guarantee success. Rather,
marketing research helps to reduce the uncertainty surrounding the
decisions to be made. In order to do so effectively, marketing research has
to be systematic, objective and analytical.
1.5 EXERCISE
Fill in the Blanks
1. _________refers to a systematic design, collection, analysis and
reporting of data and findings relevant to a specific marketing situation
facing the company.
a) Marketing Mix b) Marketing Event c) Marketing Research d)
Marketing Informati on
2. _____ data is the first -hand information collected by the researcher
a) Preliminary b) Present c) Prevalent d) Primary
3. ______ data refers to the data which is easily available.
a) Salient b) Secondary c) Scatter d) Seasonal
4. Marketing research might _____the decision -making process.
a) Delay b) Disqualify c) Prohibit d) Debar
5. Marketing research is only an ____ to decision making.
a) Obstruction b) Aid c) Hindrance d) Obstacle munotes.in
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17 Answers:
1. Marketing research
2. Primary
3. Secondary
4. Delay
5. Aid
Match the column
Column A Column B
1. Applied research A. Limitations of marketing
research
2. Not pure science B. Steps in marketing research
3. Assist in decision making C. Feature of marketing research
4. Data collection D. Ethics in marketing research
5. Right to privacy E. Functions of marke ting research
Answers:
1. C, 2. A, 3. E, 4. B, 5. D
True or False
1. Marketing research is a systematic process.
2. Cultural bias is a limitations of marketing research.
3. Managers cannot take effective decisions with the help of marketing
research.
4. Marketing r esearch is one time activity.
5. Other functional department in the organization does not benefit
from marketing research.
Answers:
1. True
2. True
3. False
4. False
5. False
Shorts Notes
1. Characteristics of marketing research.
2. Functions of marketing research department.
3. Importance of marketing research.
4. Disadvantages of marketing research.
5. Ethics in the field of marketing research.
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18 Answer in Brief
1. Define the term Marketing Research and Explain it features
2. Evaluate various functions performed by marketing researcher.
3. Discus s the significance of marketing research.
4. “Marketing Research play a crucial role in marketing decision
making”. Substantiate.
5. What is marketing research? Discuss it imitations.
6. Discuss in detail steps in marketing research process.
7. Critically evaluate eth ics related to marketing research.
1.6 REFERENCES:
Online Library:
1. https://ndl.iitkgp.ac.in/
2. https://www.britishcouncil.in/library/online -library
3. http://infolibrarian.com/dlib.html
Websites:
1. https://dictionary.cambridge.org/dictionary/english/market -resea rch
2. https://www.collinsdictionary.com/dictionary/english/market -research
3. https://www.insightsassociation.org/issues -policies/mra -code -
marketing -research -standards
4. https://www.investopedia.com/terms/m/market -
research.asp#:~:text=Market%20research%20is%20the %20process,in
%20the%20product%20or%20service.
5. https://www.yourarticlelibrary.com/marketing/marketing -research -
meaning -definition -and-objectives -explained/25862
6. https://www.economicsdiscussion.net/marketing -management/what -is-
marketing -research/31835
7. https: //www.entrepreneur.com/encyclopedia/market -research
8. https://courses.lumenlearning.com/boundless -marketing/chapter/the -
market -research -process/
9. https://businessjargons.com/marketing -research.html
10. https://smallbusiness.chron.com/types -marketing -research -exam ples-
21474.html
11. https://www.businessmanagementideas.com/marketing -
management/ethics -in-marketing -research/ethics -in-marketing -
research/18411
12. https://www.sciencedirect.com/science/article/pii/ S0167811697000098
13. https://blog.marketresearch.com/8 -leading -exper ts-share -their-top-
market -research -tips-for-2018
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19 2
INTRODUCTION TO MARKETING
RESEARCH - II
Unit Structure
2.0 Objective
2.1 Introduction
2.2 Career Options in Marketing Research
2.3 Qualities of a good marketing research professional
2.4 Marketing Information System
2.5 Summary
2.6 Exercise
2.7 Refere nce
2.0 OBJECTIVE
After studying this unit, the students will be able to:
Explore career options in the field of marketing research and essentials
qualities required to become effective marketing research
professionals.
Understand Marketing Information Sy stem, its components, Decision
Support System and Data mining
2.1 INTRODUCTION
Marketing research is dynamic in nature and continueschanges takes place
in the world of marketing research. With the advancement of Information
and technology, the various seg ments of marketing research have evolved
significantly.
There is an ample of career options in the marketing research and there is
an urgent need of well qualified, trained professionals in the various
segments of marketing research. The managers can take effective
decisions with the help of management information system. The well -
defined decision support system reduces the work of managers drastically
and it improves quality of decision making in the organization. The latest
development of in the area of data mining is major boon for the marketing
research.
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20 2.2 CAREER OPTIONS IN MARKETING RESEARCH
The key responsibility of a market researcher is to help an organization
draft a dynamic productprofile that captures the preferences of their
consumers. This in turn helps the marketing and sales teams meet their
objectives. Additionally, marketing researchers also analyse the past
statistical sales data to predict the prospect of future sales. To do so,
Market Research Analysts deploy various creative ways suc h as focus -
group interviews, surveys and telephonic interviews to get the desired
information from customers. The data collected is compiled and organized
in a systematic manner and presented to clients to take business decisions
accordingly.
Depending upo n the role, position and experience of a candidate, the
salary structure for Research professionals in a marketing research
organization can vary from post to post, educational qualifications and
work -experience. For instance, the starting salary of a fiel d survey
executive will be in the range of Rs.6,000 to Rs.7,000 per month and the
salary of a Senior Manager is up to the Rs. 9,00,000 and Rs. 15, 00,000
per annum.
1. Research Director: This is the most senior position in
marketingresearch and takes the enti re responsibility for developing and
delivering all the market research related projects on time.
2. Research Manager: Research Managers are responsible for
designing, implementing and managing the respective research projects.
They make sure that the resear ch project is running flawlessly and for that
matter liaises with the operational director. They act as a bridge between
the company and its clients.
3. Research Executive: A Research Executive takes part in the initial
development of projects and also works with the operational department of
the firm. The executive closely works with the research manager and
research analyst to develop the layout of research design and data
collection. They are also involved in the preparation of the final research
report.
4. Research Analyst: They look after the work of data analysis and
data presentation. In addition, they also play an important role in testing
the quality of questionnaire routing.
5. Operations Director: The position of operational director is full of
responsi bilities and considered the most crucial one in marketing research.
They look after a number of departments that includes sampling, data
preparation, data entry, questionnaire scripting, tabulations and the
telephonic unit. They ensure the research project is delivered flawlessly
and on time, meeting all the cost constraints and quality standards.
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21 6. Fieldwork Managers: Thefieldwork managers look after all the
recruitment, management, training and evaluation of face -to-face and
telephonic interviews. Moreove r, they have the responsibility of training,
quality management and creation of relevant research samples.
7. Data Processing Professionals: They mainly focus on one or many
core areas of data processing, which includes scripting of surveys, data
processing tabulation, statistical sampling and market modelling.
There is no second opinion now that, through the help of proper marketing
research projects any business company can know all the details regarding
SWOT i.e Strengths, Weaknesses, Opportunities and Thr eats regarding its
business beforehand and thus, it can take all the necessary and preventive
steps in advance for its continuous business growth.
2.3 QUALITIES OF A GOOD MARKETING RESEARCH
PROFESSIONAL
1. Analytical Skills: A marketing research professional should possess
strong analytical skills. It is not only important to collect the data but also
to give meaningful sense to it. The research professionals should analyse
and translate this information into actionable insights for client’s business.
2. Commu nication Skills: It is imperative for marketing research
professionals to have good verbal and written communication skills. The
researcher would be able to communicate finding of the research in simple
and clear language to client. It will help in better understanding of the
research which in turn facilitates effective decision -making process.
3. Pleasant Personality: A pleasant personality is one of the required
traits of effective marketing research professional. Although, it is
subjective in nature. It i s not mere physical personality but more emphasis
is on mental personality. As a marketing research professional, there is
need to collect information from the responded. A good blending of heart
and mind on part of research professional make good rapport with
respondents. It facilitates research professionals to work with variety of
respondents with different personality.
4. Open Minded: A marketing research professionals should have
open mind. They should not have any preconceived notion about a
particular client before working with them to reduce any potential risk of
being biased. In addition, an effective market researcher will not ask
questions that can directly affect the answers of its participants or subtly
lead participants to give outdesired answers .
5. Understanding of Multiple Research Methods: A marketing
research should be well versed with different types of research methods.
The world of market research is composed of several research
methodologies. Each one has its own corresponding benefit and munotes.in
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22 shortcoming. Marketing research professional need to distinguish when to
use which method depending on a range of situations.
For instance, focus group discussions provide a detailed opinion from
selected people in a social environment, whereas an in -depth interview is
an opinion taken from specific individuals at a time. Diary and journal
studies ensure in -the-moment reflections from individual participants
while online research communities include a bigger set of respondents
which allows for comparative analysis.
6. Client Focused: A marketing research professional must remember
that every project is different. There is no such thing as a “one size fits all”
solution in research. Marketing research professional must be able to
assess client’s problem first, understand where the gap is, and then
determine the approach and the tools required for that particular project.
Furthermore, research professionals are not restricted for using just one
research method; in fact, it is recognized that using multiple met hods and
tools can help achieve reliable results. Basically, a skilled researcher
knows how to adapt based on their client’s needs.
7. Presentation and Reporting Skills: The task of market researcher
just doesn’t end with interpreting the collected data. Wha tever insight is
drawn from the analysis phase should be well -documented, actionable,
and be made into a visually understandable report that clients will have no
problem understanding it.
As a market researcher, itis also expected to accurately present t hese data
toclients and be ready for follow -up questions. This will act as a guiding
light to help them make informed decisions. It is, therefore, really essential
to possess reporting and presentation skills.
8. Management Skills: A marketing research prof essionals need to
work with a number of people; colleagues, respondents, marketing people,
the client. It is then imperative to have strong management skills because
this work demands a strong group dynamic. They should be in position to
manage people effe ctively and do always be open for receiving and
providing feedback respectfully.
9. Spotting Trends: An effective market researcher is someone who is
able to easily spot patterns and trends through data analysis and be able to
identify meaningful events or insights from them. This refers to ability to
formed sensible conclusions from various types of observations that will
assist clients to make informed decisions.
10. Curiosity: A marketing research professional should always have
the curiosity and the desire to learn and know more. It’s important that
researcher never stop asking why and figuring out the how’s. They should
have the passion to always dig deeper, look further, and see things from a munotes.in
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23 different perspective so they can come up with ideas that client wouldn’t
have thought of.
Great marketing research professionals will continuously look for ways to
improve their knowledge of research methods and ways to innovate and
drive the industry forward.
2.4 MARKETING INFORMATION SYSTEM
Marketing information systems are really the frameworks used for
managing, processing and accessing data. They can be simply a sharing of
information by key departments, but are more likely to be some form of
integrated system based around information technol ogy. The important
issue is that the information from such a system is presented in a way that
is useful to the marketing decisions.
The term ‘marketing information system’ or MIS is used to describe such
a system. Such systems are generally discussed in the context of mark eting
information or marketing research.
2.4.1 Definition
Cundiff, Still and Govoni define MIS as, “Marketing information system
is an organised set of procedures, information handling routines and
reporting techniques designed to provide the information r equired for
making marketing decision.”
K. Cox and K. Gonod hold, “MIS is a set of procedures and methods for
the regular and planned collection, analysis and presentation of
information in making marketing decisions.”
Professor Alder Lee opines “Marketing i nformation system is an
interacting, continuing, future oriented structure of people, equipment and
procedure designed to generate and process an information flow which
can aid business executives in the management of their marketing
programmes.”
2.4.2 Com ponents of Marketing Research System
Marketing Information System (MIS) collects, analyses, and supplies
relevant information to the marketing managers. It is a val uable tool for
planning, implementing and controlling the marketing activities.
The role of MIS is to identify what sort of information is required by the
marketing managers. It then collects and analyses the information. It
supplies this information to the marketing manager at the right time. MIS
collects the information through its subsystems. These subsystems are
called components.
The four main components of Marke ting Information System (MIS) are:
1. Internal Records
2. Marketing Intelligence munotes.in
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24 3. Marketing Research
4. Marketing Decision Support System
1. Internal Records: The first compo nent of MIS is ‘Internal Record’.
Marketing managers get plenty of information from the internal -records of
the company. These records provide current information about sales, costs,
inventories, cash flows and account receivable and payable. Many
companie s maintain their computerized internal records.
The heart of the internal record sys tem is the order -to-payment cycle.
Customers send orders to the firms. The sales department pre pares
invoices and transmits copies to various departments. The billing
department sends invoices as quickly as possible. This record becomes a
vital source of information for analysis of sales, inventory levels, profit
margins, credit policy to customers, etc.
2. Marketing Intelligence: The second component of MIS is
‘Marketing Intelligence’. It collects information from external sources. It
provides information about current marketing environment and changing
conditions in the marke t. This information can be easily gathered from
external sources like; magazines, trade journals, commercial press, so on.
This information cannot be collected fro m the Annual Reports of the
Trade Association and Chambers of Commerce , Annual Report of
Companies, etc. The salesmen’s report also contains information abou t
market trends.
The information which is collected from the external sources cannot be
used directly. It must be first evaluated and arranged in a proper order. It
can be then used by the marketing manager for taking decisions and
making policies about m arketing. So, marketing intelligence is an
important component of MIS.
3. Marketing Research: The third important component of MIS is
‘Marketing Research’. Marketing research is conducted to solve specific
marketing problems of the company. It collects data about the problem.
This data is tabulated, analysed and conclusions are drawn. Then the
recommendations are given for solving the problem. Marketing research
also provides information to the marketing managers.
It acts as a tool for accurate decision -making in marketing. It is useful for
studying and solving different marketing problems. Marketing research
techniques are used by manufacturers, exporters, distributors and service
organizations. Marketing research is an applied knowledge. Hence, it
provides alternative solutions to deal with a specific problem.
However, this information is specific information. It can be used only for a
particular purpose. Marketing Information System and Marketing research
are not substitutes of each other. The scope of ma rketing information
system is very wide. It includes marketing research. However, the scope of
marketing research is very narrow. munotes.in
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25
4. Marketing Decision Support System: A growing number of
organizations are using marketing decision support system to help the
managers in taking better decisions. It is a system supported by software
and hardware to gather information from business and environment.
It helps manag ers in providing evidence for the decisions taken by them.
The current marketing software pro grams a ssist in designing marketing
research studies, market segmentation, selling prices, budget, analysing
media, and planning sales force activity.
The following are some examples of Marketing Information System
Transaction Processing System , which processes t he routine
transactions associated with a business. For example, transactions
include payroll processing, order processing, such as for an e -
commerce business, and invoicing.
Management Support Systems , which store and organize data,
enabling end users to generate reports and analyse data to address
business needs and inform planning. A data warehouse is an example of
a Management Support System.
Decision Support Systems , which analyse business data to assist
managers with decision making. For example, a DSS could project
revenue figures based on new product sales assumptions.
Expert System s, which provide managers with insights and advice,
using artificial intelligence ( AI) to simulate the expert knowledge of a
human in a particular field.
2.4.3 Essentials of Good Marketing Information System (MIS)
1. Unified and Centralized: MIS must be unified and centralized. It
collects and stores different types of market information. All of this
information must be unified and centralized. All the marketing
information must be brought together (unified) and kept at one c entral
place (centralized). So, it must be at the central -office. This will result in
easy access and quick reference. The managers will be able to find all the
required information at one place.
2. Assist Decision Making: MIS must facilitate decision making . It must
guide the marketing managers in decision making. It must provide
required information to the managers to help in taking decisions. This
information must be of a good quality. It must be relevant, reliable, and
up-to-date. This will result in an a ccurate decision -making process. So, it
must not only be a data bank. It must play a positive role in the decision -
making process.
3. Quick and Accurate: The MIS should be user -oriented and also quick.
The information flow should be done accurately and also with speed. This munotes.in
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26 is necessary as there is information flood in the field of business world. In
addition, information should be made available quickly to managers.
Information must move with speed as information supplied late to the
department is not useful in the decision -making process. Even marketing
opportunities are lost. This clearly suggests that MIS should be accurate
and should move and operate with speed within the organization.
4. Economical: MIS should be economical as far as possible. This means
the expenditure on running the system should be minimum as the system
is not directly productive. It is a service and supporting function. For such
economy in the MIS, the principle of selectivity should be introduced in
the collection, processing, storing and supplying information in the
system. The cost of MIS should not exceed its value. The expenditure of
MIS should be minimum as far as possible. However, cost reduction
should not be at the cost of quality and reliability of information.
5. Selective: MIS should collect information that is absolutely essential
and useful in decision -making process. MIS should not be viewed as a
mere courier service department. It should sort out the information that is
really useful to the firm. This is essential when there is information flood
due to the use of electronic media of communication. Thus, information
needs of the organization should be assessed and the MIS should operate
accordingly. This avoids wastage of time and money.
6. Future oriented: MIS must be forward l ooking i.e. future -oriented. It
must not be a past -oriented one. It must give more importance to future -
oriented information. It must provide information for solving problems,
which may come up in the future. The company will be successful if their
marketi ng managers are future -oriented. The marketing managers can be
so only if the MIS is also future oriented.
7. Regularity: MIS must supply information regularly. The business
environment is changing constantly. So, the marketing managers have to
take marketing decisions continuously. Therefore, they require a regular
and continuous flow of market information. This information must be
provided by MIS. So, it must s upply information regularly to the
marketing managers.
8. Use New Techniques: Along with information explosion, information
technology is also making rapid progress. New machines, methods and
techniques are being introduced in the collection, processing and storage
of information. New techniques bring speed, updating and accuracy in the
MIS. Managers can use the MIS to the fullest extent only when the latest
techniques such as computer technology and internet service are used in
MIS itself. These newer techni ques will increase the efficiency and
accuracy of MIS. MIS will also become more economical by using new
techniques.
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27 9. Flexibility: The MIS introduced in an organization should be elastic or
adjustable. It should not be rigid. When the system is flexible, n ew
changes can be incorporated easily, quickly and smoothly. Moreover,
modern techniques can be introduced for raising the efficiency and
accuracy of the system. In brief, flexibility is one essential requisite of a
good MIS.
10. Compatible with Firm Culture: MIS should be adjusted with the
culture and level of sophistication attained by the business organization.
The MIS required by a large firm would be different as compared to one
required in a small firm even when both have to maintain their own MIS.
The M IS should be understandable to the people who have to use the
system frequently. In brief, the management should set up a MIS that will
cater to the needs of an organization and also offer operational
convenience.
2.4.4 Concept of Decision Support System ( DSS)
According to Scott Morton, "Decision support system (DSS) is interactive
computer -based system, which helped decision -makers utilise data and
models to solve unstructured problems".
A decision support system (DSS) is an information system that aids a
business in decision -making activities that require judgment,
determination, and a sequence of actions.
A decision support system (DSS) is a computerized program used to
support determinations, judgments, and courses of action in an
organization or a busi ness. A DSS sifts through and analyses massive
amounts of data, compiling comprehensive information that can be used to
solve problems and in decision -making .
The information system assists the mid - and high -level management of an
organization by analysing huge volumes of unstructured data and
accumulating information that can help to solve problems and help in
decision -making. A DSS is ei ther human -powered, automated, or a
combination of both.
A decision support system produces detailed information reports by
gathering and analysing data. Hence, a DSS is different from a normal
operations application, whose goal is to collect data and not analyse it.
In an organization, a DSS is used by the planning departmentssuch as the
operations departmentwhich collects data and creates a report that can be
used by managers for decision -making. Mainly, a DSS is used in sales
projection, for inventory and operations -related data, and to present
information to customers in an easy -to-understand manner.
Theoretically, a DSS can be employed in various knowledge doma ins
from an organization to forest management and the medical field. One of
the main applications of a DSS in an organization is real -time reporting. It munotes.in
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28 can be very helpful for organizations that take part in just-in-time
(JIT) inventory management.
In a JIT inventory system, the organization requires real -time data of their
inventory levels to place orders “just in time” to prevent delays in
producti on and cause a negative domino effect. Therefore, a DSS is more
tailored to the individual or organization making the decision than a
traditional system.
2.4.5 Components of Decision Support System (DSS)
Decision support system (DSS) is a specific class of MIS system that helps
the manager at all stages of decision -making like problem identification,
selection of relevant data, picking up the right approach and examining
alternatives.
Decision support system is a mixture of computer applications and human
component which can go through large amount of data and come up with
solutions. Many companies have adopted DSS as a part of their daily
operations activities instant of considering it is as a specialised part of
business.
Many companies are constantly down load and analysis data, budget sheet
and forecasts to constantly update their strategy. This decision support
system is static in business but its result is dynamic or constantly
changing.
A system which supports the process of decision making is known as
decision support system (DSS). This helps in supporting only and not
automating the process of decision making. With the help of decision
support system, decision maker can retrieve the information and find the
alternate solutions in the process of problem solving.
DSS aids in quality decision based on model data. Correct decision
making in business is usually dependent on quality and analysis of data
and is used to find trends, which helps in creating solutions and strategies.
DSS’s are designed for every manager to execute a specific managerial
task or problem. Generally, they help managers to make semi -structured
decisions, the solution to which can be arrived at logically. However,
sometimes, they can also help in taking complex decisions.
A decision sup port system consists of three main components, namely
database, software system and user interface.
1. DSS Database: It contains data from various sources, including
internal data from the organization, the data generated by different
applications, and the ex ternal data mined form the Internet, etc. The
decision support systems database can be a small database or a standalone
system or a huge data warehouse supporting the information needs of an
organization. To avoid the interference of decision support syste m with
the working of operational systems, the DSS database usually contains a
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29
2. DSS Software System: It consists of various mathematical and
analytical models that are used to analyse the complex data, thereby
producing the required information. A model predicts the output in the
basis of different inputs or different conditions, or finds out the
combination of conditions and input that is required to produce the desired
output.
A decision support system may compromise diff erent models where each
model performs a specific function. The selection of models that must be
included in a decision support system depends on user requirements and
the purposes of DSS. Note that the DSS software contains the predefined
models (or routi nes) using which new models can be built to support
specific type of decisions.
3. DSS User Interface: It is an interactive graphical interface which
makes the interaction easier between the DSS and its users. It displays the
results (output) of the analysis in various forms, such as text, table, charts
or graphics. The user can select the appropriate option to view the output
according to his requirement.
A manager, for example, would like to view comparative sales data in
tabular form whereas an architect creating a design plan would be more
interested in viewing the result of analysis in a graphical format.
The present -day decision support system built using the Web -based
interface provides its users some special capabilities like better
interactivity, f acility for customization and personalization, and more ease
of use.
2.4.6 Importance of Decision Support System
1. Informed Decisions: DSS is often used by top and middle level
management. Decision support systems are used to make actionable
decisions, or pr oduce multiple possible outcomes based on current and
historical company data. At the same time, decision support systems can
be used to produce reports for customers that are easily digestible and can
be adjusted based on user specifications. A decision s upport system
increases the speed and efficiency of decision -making activities. It is
possible, as a DSS can collect and analyse real -time data.
2. Wider Scope: The scope of DSS is wider. It has its use in many
industries ranging from medicine to agriculture .
For instance, a medical clinician may use a computerized decision support
system for diagnostics and prescription. Combining clinician inputs and
previous electronic health records, a decision support system may assist a
doctor in diagnosing a patient.
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30 3. Preparation of Reports: DSS assist managers in preparation of
various types of reports. A decision support system analyses and
synthesizes vast amounts of data to assist in decision -making. With this
information, it produces reports that may project reve nue, sales, or manage
inventory. A DSS system is beneficial because it can be programmed to
generate many types of reports, all based on user specifications.
For example, the DSS can generate information and output its information
graphically, as in a ba r chart that represents projected revenue or as a
written report.
4. Departmental Use: DSS system is used by different department for
their specific use. For instance, DSS is used by the planning departments
such as the operations department which collects data and creates a report
that can be used by managers for decision -making. Also, DSS is used in
sales projection, for inventory and operations -related data, and to present
information to customers in an easy -to-understand manner.
5. Model Management System: The model management system
stores models that managers can use in their decision -making. The models
are used in decision -making regarding the financial health o f the
organization and forecasting demand for a good or service.
6. Training and Development: DSS promotes training and
development within organization. For instance, there is a need to conduct
number training session on continuous basis for smooth function and
implementation DSS within organization. The training sessions improves
specific knowledge, attitude, skills required for effective use of DSS.
7. GPS Routing: GPS route planning is an example of a typical DSS.
It compares different routes, taking into a ccount factors such as distance,
driving time and cost. The GPS navigating system also enables users to
choose alternative routes, displaying them on a map and providing step -
by-step instructions.
8. Clinical DSS: A clinical decision support system ( CDSS ) is a
software program that uses advanced decision -making algorithms to help
phys icians make the best medical decisions. Healthcare professionals
often use these to interpret patient records and test results, and to calculate
the best treatment plan. CDSS in healthcare can help providers identify
abnormalities during specific tests, as well as monitor patients after certain
procedures to determine if they are having any adverse reactions.
9. Quick Decisions: Time plays a crucial role in decision making
irrespective industry and level of management. All categories of decision
support syste ms are intended towards simplifying things and saving time.
A DSS helps a business in quickly making an effective decision by
analysing large volume of data. The time taken in studying data and munotes.in
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31 comparing the possible courses of actions is significantly r educed. The
decision time cycle gets shorter, allowing businesses to act speedily in a
given situation, ultimately reducing the time -to-market.
10. Accurate Data: An analysis and interpretation of data involves
human bias. Since each evaluator thinks differen tly, there can never be a
universal truth. A decision support system analyses data without any bias
and presents it in its accurate form. This enhances the possibility of
improved decision making.
11. Reduction of Cost: The deployment of a decision support sy stem
dramatically reduces the cost of gathering, sorting, processing and
analysing data. In fact, the cost of information storage, hardware and
computer and internet technology is falling considerably. This means the
cost of distributing decision -making te chnology even to the lower levels of
hierarchy is decreasing. The application of DSS will no longer be
restricted to the certain departments or hierarchical levels. The faster
decision making at all levels of management will help businesses to stand
out in market.
2.4.7 Data Mining
Data mining is a process used by companies to turn raw data into useful
information. By using software to look for patterns in large batches of
data, businesses can learn more about their customers to develop more
effective marke ting strategies, increase sales and decrease costs.
Data mining is the process of sorting through large data sets to identify
patterns and relationships that can help solve business problems through
data analysis. Data mining techniques and tools enable e nterprises
to predict future trends and make more -informed business decisions.
In simple words, data mining is defined as a process use d to extract usable
data from a larger set of any raw data. It implies analysing data patterns in
large batches of data using one or more software.
Data mining involves effective data collection and warehousing as well as
computer processing. For segmenti ng the data and evaluating the
probability of future events, data mining uses sophisticated mathematical
algorithms. Data mining is also known as Knowledge Discovery in Data
(KDD).
2.4.8 Importance of Data Mining
Data mining software is extensively valuabl e for business, because it helps
to reveal hidden patters for personal usage. These patterns help to improve
business relationships, because they are applied for making data analysis
and predictions that open wider business opportunities.
Data mining conc epts and techniques are beneficial for the variety of
industries such as: munotes.in
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32 Banking
Insurance
Education
Retail
Social Media
1. Help in Research: Data mining helps organization in conducting
marketing research and survey. It is useful for product research, vari ous
surveys, market research and analysis which in turn facilitates in
preparation of new marketing campaign and promotion strategies.
2. Collection of Information: Data mining facilitates firm in
collectinglarge but relevant information related to various a spects of
markets. For instance, with the help of scrapping process, it is possible to
collect information investors, investment and funds by scraping through
related websites and database.
3. Opinions of Customers: The opinions, views of customers are
really significant for the business organization. It forms bases of many
business decisions which in turn offer competitive advantage to the firm.
The information can be readily be found on different forums, blogs and
other resources where customers freely prov ide their views.
4. Scanning of Data: The collection of data and storing it simply will
not have significant value unless it is properly scanned. The process of
data scanning is important to identify the patterns and similarities
contained in data entries.
5. Marketing Strategies: Data mining facilitates marketing managers
in preparation of effective marketing strategies. For instance, a marketing
department of any company can mine data on customers using special
tools and datasets for data mining so that a co mpany can build the most
effective marketing campaign and become one of the most profitable and
competitive in the respective business field.
6. Planning and Forecasting: Data mining improves planning and
forecasting function of business organization. For in stance, the retail
industry can use authenticate data mining procedures for getting and
analysing customer behaviour and previous sales patterns in order to
decide what products and services to offer in future as well as what
business direction to choose.
7. Analysis of Competitor: In today’s competitive world, there is need
to understand competitor and their position in the market. Business should
know their strength and weaknesses. Their methods marketing and
distribution can be mined. Such analysis of comp etitor brings competitive
advantage to the firm.
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33 8. Business Decisions: Data mining enables firm in taking effective
business decisions. Data mining is used to discover patterns and
relationships in the data in order to help make better business decisions.
Data mining can help spot sales trends, develop smarter marketing
campaigns, and accurately predict customer loyalty. Specific uses of data
mining include:
Market segmentation
Customer churn
Fraud detection
Direct marketing
Interactive marketing
Market basket analysis
Trend analysis
9. Automated Prediction: Data mining automates the process of
finding predictive information in a large database. Questions that
traditionally required extensive hands -on analysis can now be directly
answered from the data.
A typical example of a predictive problem is targeted marketing. Data
mining uses data on past promotional mailings to identify the targets most
likely to maximize return on investment in future mailings.
Other predictive problems include forecasting ba nkruptcy and other forms
of default, and identifying segments of a population likely to respond
similarly to given events.
10. Identify Hidden Pattern: Data mining tools analyse large volume
of databases and identify previously hidden patterns. An example of
pattern discovery is the analysis of retail sales data to identify seemingly
unrelated products that are often purchased together. Other pattern
discovery problems include detecting fraudulent credit card transactions
and identifying anomalous data that co uld represent data entry keying
errors.
11. All Pervasive: Data mining is not only useful to commercial
organization but also to non -commercialization. Many companies dig
through volumes of data to discover patterns about their customers and
products. AT&T, A .C. Nielson, and American Express are among the
growing ranks of companies implementing data mining techniques for
sales and marketing. These systems are scanning through terabytes of
point -of-sale data to aid analysts in understanding consumer behaviour
and promotional strategies.
For example, In US, grocery chains have found that when men go to a
supermarket to buy diapers, they sometimes walk out with a six -pack of
beer as well. Using that information, it's possible to lay out a store so that
these item s are closer.
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34 Similarly, financial analysts are digging through vast sets of financial
records, data feeds, and other information sources in order to make
investment decisions. Health -care organizations are examining medical
records to understand trends of the past so they can reduce costs in the
future.
2.5 SUMMARY
Today many companies no longer think of marketing research in terms of
only a single project. Through experience managers have learned that they
need certain kinds of information at regular i ntervals of time in order to
deal with recurring decisions. As a consequence, they have found it very
helpful to use several regularly scheduled research projects that support or
complement one another in providing managers with the appropriate
information needed for those recurring decisions.
When a company begins to regularly schedule the coordination of findings
from several research projects designed to assist in specific recurring
decision situations, the company has begun to develop a marketing
inform ation sys tem- MIS for short.
Data mining has applications in multiple fields, like science and research.
As an application of data mining, businesses can learn more about their
customers and develop more effective strategies related to various
business fu nctions and in turn leverage resources in a more optimal and
insightful manner. This helps businesses be closer to their objective and
make better decisions.
2.6 EXERCISE
Fill in the Blanks
1. ________is a component of MIS.
a) Niche marketing b) Event mark eting c) Marketing research d)
Consumer behaviour
2. Data available from sources within the organization are called _____
sources.
a) Independent b) Index c) Internal d) Indiscreet
3. __________ consists of people, equipment’s and procedures to
gather, sort, ana lyse, evaluate and distribute needed, timely and
accurate information to marketing decision makers.
a) Marketing Identification System b) Marketing Procedural
System c) Marketing Research System d) Marketing Information
System
4. __________is a co - ordinate co llection of data, systems, tools and
techniques with supporting software and hardware. munotes.in
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35 a) Marketing Price Support System b) Marketing Decision Support
System c) Marketing Information Support System d) Marketing
Dynamic Support System
5. MIS should be a ____ system.
a) Uncordial b) Unified c) Unconvincing d) Uncommon
6. MIS should be _____ in nature.
a) Flexible b) Stiff c) Rigid d) firms
7. A properly designed MIS supplies such information which helps in
_____decision making. a) Quality b) Inferiority c) Weak d) Fra ils
8. A company needs efficient MIS to make use of ____ information.
a) Vague b) Indistinct c) Latest d) Hazy
9. A ___ is a computer application used to support determinations,
decisions, and courses of action in an organization or a business.
a) Decision Support System (DSS) b) Transaction Process
System c) Executive Support System c) Technical Support System
10. ______increases the speed and efficiency of decision -making
activities, automates managerial processes and improves
interpersonal communication within the o rganization.
a) Decision Support System (DSS) b) Transaction Process
System c) Executive Support System c) Technical Support System
11. _____ is actual discovery phase of knowledge.
a) Data mining b) Data Discovery c) Data storage d) Data
security
12. _____ is used as a synonym for data mining.
a) Knowledge discoveryb) Data warehousing c) Regression
analysis d) Parallel processing
Answers:
1. Marketing research
2. Internal
3. Marketing Information System
4. Marketing Decision Support System
5. Unified
6. Flexible
7. Quality
8. Lates
9. Decision Sup port System (DSS)
10. DSS
11. Data Mining
12. Knowledge discovery
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36 Match the column
Column A Column B
1. Analytical Skills A. Career options in the field of
marketing research
2. Research Analyst B. Specific class of MIS
3. Internal records C.Skills of effective marketing
research professional
4. Decision Support System D.Converting raw data into
meaningful information
5. Data mining E. Components of MIS
Answers:
1. C, 2. A, 3. E, 4. B, 5. D
True or False
1. A company does not need efficient MIS to make use of latest
informati on.
2. A decision support system is a procedure that allows a manager to
interact with data and method of analysis; to gather, analyse and
interpret information.
3. An imperfectly designed MIS supplies such information which enables
quality decision making.
4. Data available from sources within the organisation are called internal
sources.
5. Data Mining is defined as the procedure of extracting information
from huge sets of data
6. A Decision Support System (DSS) is an application for information
systems that helps i n decision making.
7. A decision support system differs from an ordinary operational
application.
8. A DSS always responds quickly to decision makers to help in decision
making.
9. The primary purpose of using a DSS is to present information to the
customer in an e asy-to-understand way.
10. Data transformation is also known as data mining.
Answers:
1. False
2. True
3. False
4. True
5. True
6. True
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Introduction to Marketing
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37 8. True
9. True
10. False
Shorts Notes
1. Traits of effective marketing research professionals.
2. Components of MIS.
3. Significance of Decision Support S ystem.
4. Advantages of Data mining.
5. Career options in the field of marketing research.
Answer in Brief
1. What are the various career options in the field of marketing
research? Explain.
2. Elaborate on qualities of a good marketing research professional.
3. Define Marketing Information System and discuss its components.
4. Explain in detail essentials of good marketing information system.
5. Discuss the concept of decision support system and also explain its
various components.
6. Explain the importance of decision support s ystem.
7. What is Data Mining? Explain the relevance of data mining in the
present context of business environment of India.
2.7 REFERENCE
Online Library:
1. https://ndl.iitkgp.ac.in/
2. https://www.britishcouncil.in/library/online -library
3. http://infolibrarian.com /dlib.html
Websites:
1. https://economictimes.indiatimes.com/definition/data -mining
2. https://www.ibm.com/cloud/learn/data -mining
3. https://www.insightsassociation.org/issues -policies/mra -code -
marketing -research -standards
4. https://corporatefinanceinstitute.com/res ources/knowledge/other/deci
sion-support -system -dss/
5. https://www.jagranjosh.com/articles/market -research -an-upcoming -
career -option -1517230141 -1
6. https://thebusinessprofessor.com/principles -of-marketing/decision -
support -system -explained munotes.in
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38 7. https://www.investoped ia.com/terms/m/market -
research.asp#:~:text=Market%20research%20is%20the%20process,i
n%20the%20product%20or%20service.
8. https://businessjargons.com/marketing -research.html
9. https://www.businessmanagementideas.com/marketing -
management/ethics -in-marketing -resear ch/ethics -in-marketing -
research/18411
10. https://www.sciencedirect.com/science/article/pii/ S0167811697000098
11. https://blog.marketresearch.com/8 -leading -experts -share -their-top-
market -research -tips-for-2018
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39 Module II
3
PLANNING RESEARCH - I
Unit structure
3.0 Objective
3.1 Introduction
3.2 Research Design
3.3 Hypothesis
3.4 Questionnaire
3.5 Summary
3.6 Exercise
3.0 OBJECTIVE
1. To make students familiar with the art of using various data collection
tools in Market
2. To make aware about research methodology to be used in research
3. To enable researcher to understand about sampling methods
3.1 INTRODUCTION
A research design is basically the arrangement of the condition for the
collection and analysis of data in a format that focuses to combine
relevance to the research purpose with economy procedure. A research
design is the set of methods and process which is used in collecting and
analyzing measures of the variables specified in the problem. Research
design is the conceptual structure in which the research is conducted.In
short it is a blue print of collection measurement and analysis of data.
Research design helps to understand the process or the outline in which
research will be carried out. It also helps t o provide answers to the
multiple questions like – what techniques will be used to collect the data?
what kind of sampling will be done? How time and cost constraints be
dealt with? etc. Essentials of research design are that the design should be
an activi ty and time -based plan. It is always based on the research
questions. It also helps in selection of sources and type of information. It
also indicates the framework for specifying the relationship among the
study variables. It outlines procedure for every research activity. It must
be appropriate, efficient and economical. It should be flexible and it also
must be adequate. So basically, research design refers to the framework of munotes.in
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40 market research method and techniques that are selected by a researcher
under a research design between different type of research methods,
experimental studies or quasi – experimental review study.Research
design is the whole plan for studying the conceptual research problems.
Research design is the process of collecting informati on studying it
analyzing it and maintaining the proper structure to get the proper
conclusion best research design helps best report writing.
First step in the research process is to define the problem then the second
step is to decide the objectives of th e research then the formulation of the
hypothesis is done after the formulation of hypothesis then the ideal
research design is selected. Once the research design is selected then the
sampling is done proper sampling method is decided. After the sampling
questionnaire is framed in order take the survey. After the survey all the
accurate data is collected. Then the processing of data is done. After the
processing the analysis and interpretation of data is done then hypothesis
which is used is tested. After a ll this process then the report is made. It is
called as a report writing. Reports are made after finding the conclusion
which is obtain through research.
3.2 RESEARCH DESIGN
Research design can be considered as a format in which research is going
to take place. It acts like a glue which brings all the parts of research
project together. In short it is a plan of research work or a structure in
which research is conducted.
3.2.1 Definition
According to the J ahoda, Deutch & Cook “A research design is the
arrangement of condition for the collection and analysis of data in a
manner that aims to combine relevance to the research purpose with
economy and procedure”.
Research design is the process or the structured in which research is
conducted and strategy and i nvestigation is done to search question and
control variance.
According to Kerlinger Research design is the plan, structure and
strategy of investigation conceived so as to obtain answers to research
questions and to control variance.
According to Green an d Tull A research is the specification of methods
and procedures for acquiring the information needed.
Henry Manheim says the research design not only anticipates and
specifies the seemingly countless decisions connected with carrying out
data collection, processing and analysis but it presents a logical basis for
these decisions.
In research design right information should be collected proper
interpretation should be done with economy and procedure. munotes.in
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41 3.2.2 Importance of Research Design
It helps the researc her to make correct decisions in each and every step
of the study.
It helps to identify the minor and major tasks of the study.
Based on research design a researcher can easily frame the objectives
of the research work.
Research design makes the research s tudy effective and interesting by
providing minute details at each step of the research process.
It helps the researcher to complete all the tasks even with limited
resources in a better way
A good research design helps the researcher to complete the objec tives
of the study in a given time and facilitates getting the best solution for
the research problems.
The main advantage of a good research design is that it provides
accuracy, reliability, consistency, and legitimacy to the research
It furnishes the min imum information required for planning the
research project
It enables the researcher to have a frame of reference and prevent the
study from deviating.
The research design furnishes a clear idea as to the activities that
would need to be undertaken in ord er to achieve the research objective.
3.2.3 Types of research design
A researcher must have a clear understanding of the various type of
research design to implement a study of research design which can be
broadly classified into three categories.
1. Research design in case of explanatory research studies.
2. Research design in case of descriptive research studies
3. Research design in case of casual research studies.
Explanatory research design
Explanatory research design helps in formulating the problem for more
accurate investigation or actual working on development of the hypothesis
from an operational point of view.
The main emphasis is to discovery of ideas which should be flexible
enough for providing opportunities for considering different aspects of the
problem under studies.
It will help the researcher to answer the questions such as what is the
problem munotes.in
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42 What is the aim of the study?
what topic could be studied?
To carry out this kind of research usually there is no prior research done
the existing resea rch would not able to answer all the problem precisely.
The most popular methods of explanatory research are:
Literature research
In-depth interview
Focus groups
Case studies
Descriptive Research
Descriptive design helps researcher in understand the resear ch in a better
way. Researcher is concerned in describing the situation or case under
their research study. Descriptive research studies are precisely concerned
with theory -based design method which is done by gathering, analyzing,
and presenting collected data . In other words,descriptive research
primarily focuses on narrating the nature of a demographic segment
without focusing on why a certain phenomenon occurs. If the problem
statement is not clear, one can conduct exploratory research. These
research m ethod design enables others to understand the actual importance
of research.
Casual Research studies .
Experimental research design is used to establish a relationship between
the cause and effect of a situation. It is a research design in which the
effect caused by the independent variable is observed. It is very crucial
for experimental research to create cause and effects of a phenomenon.
The effects which are observed from an experiment are due to the cause.
There are various types of research designs the major types are descriptive
research design, experimental research design, correlational
researchdesign, diagnostic research design, and explanatory research
design.
Correlational Research Design
Correlational method reveals the direction of a connect ion between two or
more than two variables. It helps the researcher to understand correlational
research design and it looks into correlations between variables without
allowing the researcher to control or manipulate any of them.
Correlational study desig n might have either a positive, negative or zero.
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43 Examples of correlation
In case of Positive correlation Both variables change in the same direction
if the prices of petrol/Diesel increase, the fare of Taxi will increase too.
In case of Negative correl ation, the variables change in opposite directions
As Tea/coffee consumption increases, fatigue decreases.
In case of Zero correlation there is no relationship between the variables
example, consumptionof Tea is not correlated with weight /Height of the
person.
Diagnostic Research Design
Diagnostic research design is a type of research design that tries to
investigate the fundamental reason of a certain condition. This method
assists a researcher more about the factors that contribute to certain
difficultie s or challenges that others may be experiencing. This design
consists of three research stages
1- Inception of the issue
2- Diagnosis of the issue
3- Solution for the issue
Experimental design
Experimental design in simple words is the blueprint of the procedure
that allows the researchers to control all the factors of the experiment.
Experimental design is often used when there is a priority of time such
as cause will always precede effect and when there is stability in a causal
relationship such as a particular ca use will always lead to the same
effect and the degree of association is great.
Merits of using experimental design
1. It delivers a high level of evidence for research
2. Experimental design determines the cause of something to take place
3. Experimental design he lps researchers to determine effects.
Demerits of experimental design
1. Experimental research may not fit all the time in practical world
2. The situations of the experiments may change the behavior of the
subjects.
3. Experimental researches are costly, because it need special equipment
and facilities.
4 There are a few types of problems which can’t be experimented
because of ethical
5 Sometimes technical reasons may bring problems in research. munotes.in
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44 Historical design
Research data from the past is collected in this method, evaluate and the
hypothesis is defended based on the outcomes. To use this method a lot of
resources like reports, records, logs, documents, notes, diaries, official
records, archives, and n o textual data like maps, images, drawings, audios)
are used. The accuracy of result depends upon the authentic and
authorized documents.
Merits of Historical research design
1. This method is useful for trend analysis.
2. It can provide a contextual background to understand a research
problem in a better way.
3. There are no chances of emotional involvement of the researcher with
the subject.
4. Historical resources can be used multiple times.
Demerits of Historical Research design
1. The success of research completely b ased on the quality of historical
resources.
2. Research remains weak due to lack of control on external variables
3. Gaps are difficult to measure because of the missing pieces of
historical resources.
4. Understanding of historical resources consumes a lot of ti me.
Observational research design
Observation research design is used to draw results by comparing subjects
under research with a controlled group. Two types of observational studies
are as follows.
In first caseyour subjects know that you are observing th em and in the
second type, you observe your subjects without letting them
know. Observational research design let you get the insights of a particular
phenomenon without getting into the trouble of setting up in case of large
project.
Merits of observational research design
1. Observational research is a flexible type of research and doesn’t
require to stick to a hypothesis
2. In-depth information can be collected about the phenomenon.
3. Resu lts can be generalized to real life events.
4. It can act as pre -research before starting any other experiment.
5. It accounts for the complexity of group behavior. munotes.in
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45 Demerits of observational research design
1 There are high chances for this research turned out to be biased
because the researcher might notice what he wants to notice.
2 The outcome of this research is limited to a small group and can’t be
generalized.
3 Subjects might behave differently because of the presence of the
researcher.
3.3 HYPOTHESIS
A hypoth esis is very important for the entire procedure. In simple words it
is a tentative statement about the relationship between two or more
variables. Basically, hypothesis is the statement which researcher makes
expectation or prediction about relationship am ong variables. The research
is the process which begins and ends with hypothesis.
Hypothesis is nothing else but the heart of the research. In the research
without hypothesis, research cannot service properly. The researcher
identifies the questions to st udy the concepts might be related hypothesis
is the predicted answer.
Three important factors in hypothesis are difference that we are trying to
find out, relationship and the interactions. Results are statistically
important as it plays the vitalrole.
A hypothesis ensures the entire research process remains scientific and
reliable. Though hypothesis is very much essential during the research
process it can produce complications with regards to probability,
significance and errors.
Hence hypothesis is the prediction based on the observation. Hypothesis is
usually a statement that introduces a research question and proposes an
expected result.
It is important that forms the basics of scientific experiment. Therefore, it
is very much needed to be careful whil e making hypothesis. A minor
mistake in construction of the hypothesis could have the adverse effects on
the experiment.
Research hypothesis is a specific testable prediction about the expected
things to happen in a study. Good research is the result of go od
hypothesis.
Hypothesis is generally the prediction of the study that will help to find
the empirical statement verified and based upon observation or experience.
with the help of research studyfindings Hypothesis is testable whether it is
true/false
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46 3.3.1 Types of hypotheses
There are various types of hypotheses and they are simple hypothesis,
complex hypothesis, directional hypothesis, non -directional hypothesis,
null hypothesis, associate and casual hypothesis.
Simple hypothesis
This type of hypothes is showcases a relationship between dependent
variable and a single independent variable. For example, if you eat more
of vegetables will help you lose weight faster. Here eating vegetables in
huge amount is the dependent variable.
Complex hypothesis
In th is type it shows how the relationship between two or more dependent
variables and also two or more of independent variable. In this hypothesis,
the dependent and independent variables are more than two. For example,
if you eat more of vegetables and fruits it will lead to weight loss, glowing
skin, reduces the risk of many diseases such as heart disease, high blood
pressure and some cancers.
Directional hypothesis
In this type of hypothesis, it represents how a researcher is committed to
particular outcome. Relationship among the variables can also predict its
nature. For example, children who four -year-old are eating moderate and
adequate food over the five years of period are proven that having higher
IQ level than children who are not having proper meal. This indicates the
effect and the direction of the effect.
Non directional hypothesis
This type of hypothesis is used when the theory is not involved. In this
type of hypothesis there is a statement that a relationship exists between
two variables without doing prediction of the exact direction of the
relationship.
Null hypothesis
This is the type of hypothesis which provides the statement that is contrary
to the hypothesis. Basically, it’s a negative kind of statement and there is
not any relationship amon g independent and dependent variables. The
symbol is denoted by “HO”.
Associate and casual hypothesis
In this type of hypothesis, the associative hypothesis occurs when there is
a change in one variable resulting in a change in change in the other
variable also. On the other hand, casual hypothesis gets effected and there
is cause and interaction effect among two or more variables.
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47 3.3.2 Importance of hypothesis
To the point enquiry
It makes the research activity to the point and destination. Research
without hypothesis is like a sailor in the sea without compass . So,
research is to the point enquiry of problem due to the guidance of
hypothesis.
Separating Relevant from Irrelevant Observation
A Researcher during study will take the observations and facts w hich are
accordance to the condition and situation. While drop out the irrelevant
facts from his study. This separation is due to hypothesis formulation
which keeps away relevant observation from irrelevant.
Development of Research Techniques
There are various types of social problems which are complex in
nature . For this research is very difficult. We cannot cover it with a single
technique but it requires many techniques. These techniques are due to
hypothesis provided to a researcher.
Acts as a Guide
Hypothesis gives new ways and direction to a researcher. It acts as a guide
and a leader in various organizations or society. It is l ike the investigator’s
eye.
Selecting Required Facts
During study a researcher come across many factors but he confined
himself to the selection of required facts through formulation of
hypothesis. Hypothesis helps him in selection of relevant facts
regarding to the problematic situation
Prevents Blind Research
Hypothesis provides lighting to the darkness of research. It gives
differ ence b/w scientific and unscientific, false and true research. It
prevents blind research and give accuracy.
Accuracy & Precision
Hypothesis provides accuracy and precision to a research activity.
Accuracy and precision are the feature of scientific invest igation which is
possible due to hypothesis.
Save Time, Money & Energy
Hypothesis save time, money and energy of a researcher because it is a
guide for him and help him in saving these basic things.
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48 Proper Data Collection
Hypothesis provides the basis of proper Data Collection Relevant and
correct information collected by a researcher is the main function of a
good fo rmulated hypothesis .
Proper Conclusion
A proper formulated hypothesis may lead to a good reasonable, utilized
and proper conclusion. If the hypothesis is better than the conclusions
drawn by a researcher would be better for solution of a problem.
Hypothesi s is very much important in research because helps in many
ways it helps to replicate the research, draw the logical conclusion and
also helps to maintain the relation between the variables, it provides the
statement deduced from theory, it helps to select the fact, it also provides
the direction to the research.
Hypothesis are very important as it helps to ensure entire research
methodologies which are scientific and completely valid.
It also helps to forecast the possibility of research failure and progr ess.
It also helps to narrate the whole research study in concrete terms rather
than describing them in theoretical terms.
It also helps in providing the foundation and evidence to prove the validity
of the research.
It also provides the link to the theori es which are underlying and also to
the specific research questions.
It plays a vital role in data analysis and also in measuring the validity of
the research.
Hypothesis is very important as it helps to create efficient reports, it gives
clarity, it also provides solution to various problems, it has the power of
prediction and many more.
3.4 QUESTIONNAIRE
Questionnaire is a list of questions which are asked to the individual to
obtain statistically useful information for the topic which is given.
Questionn aire are mostly used in the research to collect information.
Questionnaire are usually used in the quantitative marketing and social
research. When the questionnaire is frame in a proper order then it
becomes a vital instrument through which statement can be made about
specific groups or entire population.
It is the most valuable method of collecting data in wide range. For the
success of the survey moderate construction of questionnaire is important.
This kind of survey helps to collects the information in large number. munotes.in
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49 The definition of questionnaire is “A questionnaire is simply a list of
mimeographed or printed questions that is completed by or for a
respondent to give his opinion.
A questionnaire is very important source of collecting quantitative prima ry
data. A questionnaire allows quantitative data to be collected in a
standardized format so that data is consistent for analysis. Questionnaire
should always have a purpose which is related to the objective of the
research. It should be very clear, prec ise and accurate.
Questionnaires are used when the resources are limited, confidentiality
should be maintained in order to get honest responses for the best results.
3.4.1 Types of Questionnaires
Questionnaire is classified in qualitative and quantitative method it usually
depends upon the nature of the questions.
Questionnaire is the primary method of data collection. There are the
following types of Questionnaires:
Characteristics of a good questionnaire
Data depends on the type of information researcher need to collect from
respondents. In case of exploratory research Qualitative questionnaires are
used by the researcher. Quantitative questionnaires are used to validate or
test a previously generated hypothesis
Computer questionnaire
In this type of Quest ionnaire respondents are asked to answer the
questions which are send by mail. The benefits of computer questionnaire
are that it’s inexpensive, it saves time and respondent also don’t feel any
kind of pressure as they can reply as pe their convenience so the answers
are more reliable.
Telephone Questionnaire
In this type researcher prefers to call to the potential respondents with the
objective of getting them to answer the questionnaire. The benefits of this
are its very time convenient as it requires sho rt amount of time to ask the
questionnaire on telephone. However, many people don’t feel to answer
questionnaire over phone as they don’t feel comfortable to do so.
In house survey
In this type of survey researcher visits directly to houses or workplaces o f
the respondent to conduct the survey. This kind of survey has lots of
advantages are they are more focused towards the questions and it has
higher chances of getting reliable responses.
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50 Mail Questionnaire
In this type of questionnaire, the researcher s ends the questionnaire
through post often attaching paid envelop. It has the advantage of getting
honest and accurate feedback as the respondents replies in their free time
as per their convenience. This type of questionnaire is expensive in nature.
Open q uestion questionnaire
Open questionnaire is very different from the other questionnaire in this
the open questions may produce unexpected results. Which helps to make
research more valuable and helpful.
Multiple choice Questions
In this type of questionnai re, the respondent is given multiple options from
that they have to select as per their choices, this kind of survey is very
helpful as it is not boring and time consuming as the respondent just have
to select the options which makes easy for them to give feedback.
Dichotomous questions
These types of questions provide two options to the respondents that is yes
or no to select from. It is the easiest type of questionnaire in terms of
responding.
3.4.2 Steps in preparation of Questionnaire
Questionnaire is the instrument which is used in the research for the
collection of the information through the survey it contains a series of
questions for the respondent. The questionnaire is of various types hence
there are certain steps which are taken in the preparati on of questionnaire.
Identify a theme
It is a theme in which one can specify what kind of data needs to be
collected and how to convert it in a question format.
Ask simple questions
The questions in the questionnaire should be simple and easy to
understand it should not be complex. It should be as specific as possible.
All the respondent should able to answer each and every question without
any difficulty.
Ask the same questions in different ways
The same questions should be asking several times in differen t ways just
to check that respondent is not taking the survey absentmindedly. Because
survey should e reliable for those same questions should be ask in
different ways.
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51 Choose a delivery method.
Selection of delivery method is very much important as it helps to reach
the wide range of audience. If one wants to reach the large number of
audience one can distribute the questionnaire through various social
networks.
These are the steps which are used in the making of a Questionnaire.
3.5 SUMMARY
Research d esign is based on methodology and it should be prepared once
the topic and the problem of research have been selected and formulated
then objectives are properly framed and proper hypothesis should be made
Research design is a foundation of entire research process it is needed
because it helps in the smooth conducting various research operations,
thereby making research as efficient as possible yielding maximal
information with minimal expenditure of Time, various efforts and money.
Research design has a si gnificant impact on the reliability of the results.
Research design plays a very crucial role in facilitating and providing
smooth functioning of the entire research process. A good research design
gives good research output. It is needed for planning rese arch activities
considering time budget, human efforts, techniques, sampling etc. The
validity of the research result is based on the format of the research design.
Hence the research design has to be prepared very carefully and efficiently
as it is the ba se of the whole research process that follows the
characteristics of efficient research design hence research design should be
properly understood at first.
Hypothesis may be proved or disproveddepends upon the data collected
from respondents. It is not po ssible in case of behavioural sciences to test
multiple hypotheses at a same time.
A hypothesis is very important for the entire procedure. In simple words it
is a tentative statement about the relationship between two or more
variables. Basically, hypothe sis is the statement which researcher makes
expectation or prediction about relationship among variables. The research
is the process which begins and ends with hypothesis.
Hypothesis is nothing else but the heart of the research. In the research
without hypothesis, research cannot service properly. The researcher
identifies the questions to study the concepts might be related hypothesis
is the predicted answer.
Three important factors in hypothesis are difference that we are trying to
find out, relations hip and the interactions. Results are statistically
important as it plays the vital role
Hypothesis is very much important in research because helps in many
ways it helps to replicate the research, draw the logical conclusion, to
maintain the relation betw een the variables, it provides the statement munotes.in
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52 deduced from theory, it helps to select the fact, it also provides the
direction to the research. Hypothesis plays a vital role in research.
Hypothesis are very important as it helps to ensure entire research
methodologies which are scientific and completely valid.It also helps to
forecast the possibility of research failure and progress.It also helps to
narrate the whole research study in concrete terms rather than describing
them in theoretical terms It also he lps in providing the foundation and
evidence to prove the validity of the research.It also provides the link to
the theories which are underlying and also to the specific research
questions.It plays a vital role in data analysis and also in measuring the
validity of the research.Hypothesis is very important as it helps to create
efficient reports, it gives clarity, it also provides solution to various
problems, it has the power of prediction and many more.
Questionnaire is a list of questions which are aske d to the individual to
obtain statistically useful information for the topic which is given.
Questionnaire are mostly used in the research to collect information.
Questionnaire are usually used in the quantitative marketing and social
research. When the qu estionnaire is frame in a proper order then it
becomes a vital instrument through which statement can be made about
specific groups or entire population. It is the most valuable method of
collecting data in wide range. For the success of the survey moderat e
construction of questionnaire is important. This kind of survey helps to
collects the information in large number. The definition of questionnaire is
“A questionnaire is simply a list of mimeographed or printed questions
that is completed by or for a res pondent to give his opinion. A
questionnaire is very important source of collecting quantitative primary
data. A questionnaire allows quantitative data to be collected in a
standardized format so that data is consistent for analysis. Questionnaire
should always have a purpose which is related to the objective of the
research. It should be very clear, precise and accurate Questionnaires are
used when the resources are limited, confidentiality should be maintained
in order to get honest responses for the bes t results.
3.6 EXERCISE
Fill in the blanks
1.Researchdesign helps the researcher to identify and task of study.
A. Research designs B. Data Collection C. Variables D. Sampling
2. Researchdesign helps researcher to make in each and every step of
study.
A. Research designs B. Data Collection methods C. Independent
Variables D. Sampling Techniques
3. __________should always have a purpose which is related to the
objective of the resear cher
A. Questionnaire B. Primary Data C. Secondary Data D. Hypothesis munotes.in
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53 4. A _______________allows quantitative data to be collected in a
standardized format .
A. Primary Data B. Secondary Data C. Hypothesis D. Questionnaire
5. __________ may be proved or disproved depends upon the data
collected from respondents .
A. Prima ry Data B. Secondary Data C. Hypothesis D. Test
True or False
1. Based on research design a researcher can easily frame subject of
research work.
A True
2. Research design does not help the researcher to make correct decisions
in each and every step of study.
A False
3. Hypothesis does not act as guide.
A False
4. Hypothesis plays a vital role inresearch.
A True
5. Hypothesis does not give to the point enquiry.
A False
Match the column
1. Research a) Finding solution for
immed iate problem
2. Applied Research b) Search for knowledge
3. Questionnaire c) Heart of Research
4. Hypothesis d) Data from past is collected
5. Historical Design e) Primary Data
Answers: 1 - B 2 -A 3 -E 4 -C 5 -D
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54 Shorts Notes
1. Demerits of observational research design
2. 7 phases of research design.
3. Elements of research design.
4. Advantages of research design.
5. Need of research design.
Answer in Brief
1. Write importance of research design.
2. In which format is resear ch design conducted?
3. What is explanatory research design?
4. What is historical design? Write its merit and demerits.
5. Write types of hypotheses
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56 4
PLANNING RESEARCH - II
Unit Structure
4.0 Objective
4.1 Introduction
4.2 Essentials of questionnaire
4.3 Sampling
4.4 Summary
4.5 Exercise
4.6 Reference
4.0 OBJECTIVE
1. To make students aware about different tools used in research
2. To make aware about research planningto be used in research
3. To enable researcher to understand about questionnaire and sampling
methods
4.1 INTRODUCTION
A historically important area of planning research , although one that has
received less attention more recently, is th e role of learning. The Prodigy
system in particular is associated with this direction of research. Learning
can play a useful role in several stages of planning. Researchers have
considered several subjects here, including acquisition of operators and
domain models, learning intelligent behaviour scripts to reduce future
planning demands, learning intelligent planning strategies and learning
strategies for plan repair. Cognitive science can play a valuable role in
helping researchers to understand the role of learning in human problem
solving.
Research in planning and cognitive sciences have been on diverging paths
over recent years. However, developments in planning appear to offer the
possibility of significant new insights into relationships between huma n
and artificial planning and for these insights to contribute to the future of
both disciplines.
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57 4.2 ESSENTIALS OF GOOD QUESTIONNAIRE
It helps the researcher in what is to be measured – Having a clear
picture and understanding of what data needs to be c ollected
contributes to the quality of data collection.
Questionnaire should be neutral and should not be leading it should be
taken care of.
Emphasis on right word/phrase should be kept in mind – The language
should be clear so that the required data c an be received. It willmake
the question and the requirement of survey easy to understand and thus
help in getting a better response.
Define and qualify terms – This is most essential when a technical
survey or a field specific survey is being done. This w ill increase the
quality and decrease the bounce rate or number of questions which
were left unanswered.
Sufficient or adequate alternatives should be provided
Multiple questions in question should be avoided – One question
should have one answer. If more than one question needs to be asked
than it should be made a separate question to improve clarity of
questions.
Word requiring emphasis should be emphasized – It helps in making a
point and question clear
options like good/bad/fair/average should be quant ified through
photographs or other mean – These are very vague terms and
interpretations of these varies from person to person
Unwanted assumptions should be avoided – A survey is about getting
factual data and assumptions should be avoided.
The length of the questionnaire should be ideal.
The language which is to be used in the questionnaire should be easy,
simple and understandable.
All the terms should be explained clear and proper.
All the questions should be in a logicalformat.
The questions should be in an analytical form.
Difficult questions should be broken into filter questions.
All the questions should be explained correctly and moderately.
The questions should be structured for the specific period of time.
The answers should be short and simple.
All answers should be relevant to the problem.
Answers should be understood able to each and every respondent.
Hence questionnaire should be precise, short and simple, use of easy
language, accurate answers, there should be a logical format these are the
essentials of the good questionnaire. munotes.in
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58 4.3 SAMPLING
Sampling is a process which is used in the analysis of states in which
number of observations are taken from the larger group such as
population. The method of the sample of larger population upon the
sampl e of larger population and analysis which is to be done. Most
commonly sampling method includes random sampling or systematic
sampling. Basically, sampling is used in the selection of a group of the
population of interest in a research study. In huge resea rch the
participation of a whole population of interest is not possible, so a smaller
group depends upon for a collection.
Sampling helps in taking a portion of few materials or protect to test
chemical analysis the main purpose of quality control and iden tification.
Sampling usually gives permission to researchers to obtain sufficient date
a to answer the research question.
The sampling generally describes the minimum sampling rate at which a
continuous time signal needs to be uniformly sampled so that th e original
signal can be completely recovered.
4.3.1 Sampling
In research methodology sampling is known as the process of selecting the
smaller number of elements from the larger group to collect the
information.
Definition: a sample is defined as a smalle r set of data that a researcher
chooses or selects from a larger population by using a pre -defined
selection method.
Sampling is basically the selection of the subset of individual units from a
wide group such as population to estimate feature of the entir e population.
Statisticians usually try to collect samples that represents the population in
questions. Sampling helps to reduce cost and increase data collection that
measuring the whole population that can provide in cases where it’s not
possible to samp le whole population every observation counts one more
properly. In survey sampling factors such as weights can be applied to the
data for the sample design.
4.3.2 Terms in sampling
Population
A population is the total group of people about who you are rese arching
and about which you want to draw conclusions. Researcher must frame
sample design for study and must plan how a sample shole be selected and
what size like a sample would be.
It is common for variables in the population being denoted by Greek
letters and for those in the sample to be shown by Latin letters. For
example, standard deviation of the population is often shown with s munotes.in
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59 (sigma), whilst of a sample is 's'. Sometimes as an alternative, capital
letters are used for the population.
Sample frame
The list of people from whom you draw your sample, such as a phone
book or 'people shopping in town today', may well be less than the entire
population and is called a sample frame . This must be representative of the
population otherwise bias will be intro duced.
Sample frames are usually much larger than the sample. They are used
because of convenience and the difficulty of accessing people outside this
frame (for example those without a telephone).
Sample
When the population is large or generally inaccessi ble then the approach
used is to measure a subset or sample.
Unit
A unit is the thing being studied. Usually in social research this is people.
There may also be additional selection criteria used to choose the units to
study, such as 'people who have been police officers for at least five years.'
Sample size
In order to be representative of the population, the sample must be large
enough. There are calculations to help you determine this. The required
sample size depends on the homogeneity of the populatio n, as well as its
total size.
Generalizing
After sampling researcher generalize data in order to make conclusions
about the rest of the population.
Validity
Validity is about truth and accuracy. A valid sample is representative of
the population and will a llow you to generalize to valid conclusions. This
aligns with external validity . sample deign should be reliable and correct.
A valid sample is both big enough and is se lected without bias so it is
representative of the population.
Bias
Bias, a distortion of results, is the bugbear of all research and it can be
introduced by taking a sample that does not truly represent the population
and hence is not valid.
Assignment
Having drawn the sample, these may be assigned to different groups. munotes.in
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60 A common grouping is an experimental group which receive the treatment
under study and a control group that gives a standard against which
experimental results can be compared. To sustain in ternal validity, this is
usually random assignment . Non -random assignment is sometimes ok, for
example where two school classes are selected as coherent groups and one
chosen as the control.
Sampling fraction
When there a sample of n people are selected fr om a population of N, then
the sampling fraction is calculated as n/N. This may be expressed as a
number (e.g., 0.10) or a percentage (e.g., 10%).
Sampling distribution
If the sample is described as a histogram (a bar chart showing numbers in
different mea surement ranges) it will have a particular shape. Multiple
samples should have similar shapes, although random variation means
each may be slightly different. The larger the sample size, the more similar
sample distributions will be.
Sampling error
This is the standard error for the sample distribution and measures the
variation across different samples. It is based on the standard deviation of
the sample and the gap between this and the standard deviation of the
population. Larger sample sizes will lead to a smaller sampling error.
Systematic error
A systematic error is one caused by human error during the design or
implementation of the experiment.
Strata
Strata (singular: stratum) are sub -groups within a population or sample
frame. These can be random gro ups, but often are natural groupings, such
as men and women or age -range groups. Stratification helps reduce error.
See stratified random sampling for usage.
Oversampling - Oversampling occurs when you study the same person
twice. For example, if you selec ted people by their telephone number
and someone had two phone numbers, then you could end up calling
them twice. This can cause bias.
The art of sampling involves the two major terms subsample and
representative sample.
Sampling is the method used in stat istical analysis so these various terms
are used. Bulkmaterial, sample increment, sample, test portion, subsample,
backup sample, representative sample, homogenous material,
heterogeneous material, contiguous sampling, intermittent sampling, bias,
random s ampling. munotes.in
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61 Sample is the amount of material which is send for testing. In test portion
a small portion is need for specific test. In subsample is as same as the test
portion in this also part of the sample is used for testing. In backup sample
a subsample is taken as insurance in case the sample needs to be tested for
other reasons.
In representative sample, sample that is same in all the ways to large bulk
it was derived from homogeneous material is the materials of similar
composition and hence it is easy t o sample. In heterogeneous material the
material of non -uniform composition and hence it is very difficult to
sample. Continuous sampling is the sampling where small sample
increments are removed at regular intervals.
Intermittent sampling is usually assoc iates with batch production where
the taken from the batch.
In bias in this term any situation where a representative sample.
Random sampling is a sampling where a number of increments are taken
in a random manner.
4.3.3 Techniques of sampling
A- Simple ra ndom sample
Simple random sampling is defined as a sampling technique where every
item in the population has an even chance and likelihood of being selected
in the sample. Here the selection of items entirely depends on luck or
probability, and therefore this sampling technique is also sometimes
known as a method of chances.
Simple random sampling is a fundamental sampling method and can easily
be a component of a more complex sampling method. The main attribute
of this sampling method is that every sampl e has the same probability of
being chosen.
For example, if you randomly select 1000 people from a town with a
population of 100,000 residents, each person has a 1000/100000 = 0.01
probability. That’s a simple calculation requiring no additional knowledge
about the population’s composition. Hence, simple random sampling.
Advantages of simple random sampling
1. It is a fair method of sampling, and if applied appropriately, it helps to
reduce any bias involved compared to any other sampling method
involved.
2. Since it involves a large sample frame, it is usually easy to pick a
smaller sample size from the existing larger population.
3. The person conducting the research doesn’t need to have prior
knowledge of the data he/ she is collecting. One can ask a ques tion to
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62 4. This sampling method is a fundamental method of collecting the data.
You don’t need any technical knowledge. You only require essential
listening and recording skills.
5. Since the population s ize is vast in this type of sampling method, there
is no restriction on the sample size that the researcher needs to create.
From a larger population, you can get a small sample quite quickly.
6. The data collected through this sampling method is well info rmed; more
the samples better is the quality of the data .
B- Stratified simple random sample
Stratified simple random sampling is a variation of simple random
sampling in which the population is partitioned into relatively
homogeneous groups called strata and a simple random sample is selected
from each stratum. The results from the strata are then aggregated to make
inferences about the population. A side benefit of this method is that
inferences about the subpopulation represented by each stratum can also
be made.
Cluster sampling involves partitioning the population into separate groups
called clusters. Unlike in the case of stratified simple random sampling, it
is desirable for the clusters to be composed of heterogeneous units.
In single -stage cluster sampling, a simple random sample of clusters is
selected, and data are collected from every unit in the sampled clusters.
In two-stage cluster sampling, a simple random sample of cluster s is
selected and then a simple random sample is selected from the units in
each sampled cluster. One of the primary applications of cluster sampling
is called area sampling, where the clusters are counties, townships, city
blocks, or other well -defined ge ographic sections of the population.
C - Convenience sampling
Convenience sampling is the most common form of non -probabilistic
sampling, mostly because it is misused. Conveniencesampling is a
method of collecting samples by taking samples that are conven iently
located around a location or Internet service. We have all seen studies that
leverage students in the computer science classes. This is convenience
sampling improperly used. A proper use of convenience sampling would
be sampling of craigslist, the S ilk Road, or other black -marke t services to
study cyber -crime communication. Selectin g a set of found
communications would adequately represent other criminal
communication where computer science students do not represent the
general public very well .
For example, standing at a mall or a grocery store and asking people to
answer questions would be an example of a convenience sample.
D - Sampling systematic
Systematic sampling is a statistical method that researchers use to zero
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63 calculate the sampling interval by dividing the entire population size by
the desired sample size. Systematic sampling is an extended
implementation of probability sampling in which each member of the
group is selected at regular periods to form a sample.
Systematic sampling is defined as a probability sampling method where
the researcher chooses elements from a target population by selecting a
random starting point and selects sample members after a fixed ‘sampling
interval.’
For example, in school, while selecting the captain of a sports team, most
of our coaches asked us to call out numbers such as 1 -5 (1-n) and the
students with a random number decided by the coach. For instance, three
would be called out to be the ca ptains of different teams. It is a non -
stressful selection process for both the coach and the players. There’s an
equal opportunity for every member of a population to be selected using
this sampling technique.
E - Quota sampling
Quota sampling is a two -stage non -probability sampling method that assigns quotas to
the population in order to ensure that when elements of the population are selected, the
sample group is representative of the population’s characteristics. After quotas are
assigned, researchers c hoose elements from the subgroups using convenience or
judgment.
Quota sampling is a type of non-probability sampling method. This means that
elements from the population are chosen on a non -random basis and all members of
the population do not have an equ al chance of being selected to be a part of the sample
group.
In this method of sampling, researchers typically use market research software to
create two stages to acquire their sample group. First, they list relevant control
characteristics and their dis tribution in the target population. This is done to ensure that
the composition of the selected sample group is representative of the composition of
the target population (in regard to the listed control characteristics). These “control
characteristics” ca n be variables such as age, race, and sex. Researchers create these
groups based on their own judgement.
The second stage is to select elements for the sample group based on convenience
and/or judgement of the researcher. This is what differentiates quota sampling from
stratified sampling, as stratified sampling uses SRS (simple random sampling) or
other probability sampling methods to choose elements for the sample group once the
strata are divided.
Example of Quota Sampling
Let’s assume that a researcher w a n t s t o s t u d y t h e b u y i n g h a b i t s o f t h e p e o p l e i n
Mumbai depending on their gender and employment status. In this example, gender
and employment status will be the “relevant control characteristics”, using which the
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64 Researchers wil l then use this information to reflect similar proportions of
male/female and employed/unemployed in their sample group.
For this study, let’s say a sample size of 100 people is decided upon. Researchers will
use market research tools which have quotas to decide how many males and females
are chosen in regard to their employment status. Therefore, they may choose to
include 60 females and 40 males, 10 of which are unemployed. These elements will
be chosen by the researcher on the basis of convenience or ju dgement .
Under quota sampling method, the researcher forms a sample that involves
the individuals to represent the population based on specific traits or
qualities. The researcher chooses the sample subsets that bring the useful
collection of data that gen eralizes the entire population.
Merits
1. If quotas are allocated objectively and properly it provides satisfactory
results.
2. Each part of the population gets representation.
3. Satisfactory results are expected under this method
Demerits
1. This method is subjected to personal bias may possible under this
method
2. If the interviewers are properly trained than only satisfactorily results
can achieve.
F- Snowball sampling
Snowball sampling is a recruitment technique in which research
participants are asked to assist researchers in identifying other potential
subjects. The use of currently enrolled research participants to recruit
additional research participants it sometimes referred to as “the snowball
sampling. The method is used to minimizes risk. Snowball Sampling
In this method, the samples have traits that are difficult to find. So, each
identified member of a population is asked to find the other sampling
units. Snowball sampling is also known as a chain -referral sampling
technique. Those sampling units also belong to the same targeted
population.
G- Purposive sampling: Purposive sampling, also known as
judgmental , selective or subjective sampling, is a type of non-probability
sampling technique . Non -probability sampling focuses on sampling
techniques whe re the units that are investigated are based on
the judgement . There are a number of different types of purposive
sampling, each with different goals. This article explains what purposive
sampling is, the eight of the different types of purposive sampling, how to
create a purposive sample, and the broad advantages and disadvantages of
purposive sampling.Unlike the various sampling techniques that can be munotes.in
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65 used under probability sampling (e.g., simple random sampling, stratified
random sampling, etc.), the goa l of purposive sampling is not
to randomly select units from a population to create a sample with the
intention of making generalisations (i.e., statistical inferences ) from that
sample to the population of interest. This is the general intent of research
that is guided by a quantitative research design . The main goal of
purposive sampling is to focus on particular characteristics of a population
that are of interest, which will best enable you to answer your research
questions. The sample being studied is not representative of the
population, but for researchers pursuing qualitative or mixed methods
research designs , this is not considered to be a weakness. Rather, it is a
choice, the purpose of which varies depending on the type of purposing
sampling techn ique that is used. For example, in homogeneous sampling ,
units are selected based on their having similar characteristics because
such characteristics are of particular interested to the researcher. By
contrast, critical case sampling is frequently used in exploratory . During
the course of a qualitative or mixed methods research design , more than
one type of purposive sampling technique may be used.
H - Voluntary sampling
A voluntary response sample can be defined as a sample made up of participants who
have voluntarily chosen to participate as a part of the sample group.
Participants in a voluntary response sample usually choose to respond to surveys
because they have a strong opinion on the subject of the survey. This is why voluntary
response samples tend to give rise to significantly biased results, as most of those who
participate will have a strong opinion about a topic in either direction. Another reason
why people participate is due to the convenience of joining the survey.
Voluntary response samplin g is considered a type of non-probability sampling
technique because participants are self -chosen, and not selected by the researcher on a
random basis.
An example of a voluntary response sample is when TV show hosts of competitions,
such as the Indian Ido l, ask their viewers to send in their responses for who they think
should win the competition. Only viewers who have strong opinions on who should
win will send in their votes. Viewers who are indifferent toward the show and its
competitors will not send i n their votes .
I - Consecutive sampling
Consecutive sampling is also known as total enumerative sampling, consecutive
sampling is the process of conducting research including all the people who meet the
inclusion criteria and are conveniently available, as part of the sample. The researchers
conduct research one after the other until they reach a conclusive result, thus, the
prefix consecutive. Here, the sample is selected based on their easy availability,
research is conducted, results are obtained and ana lysed and then the researcher
moves on to the next
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66 J - Purposeful sampling
Purposeful sampling is widely used in qualitative research for the
identification and selection of information -rich cases related to the
phenomenon of interest. Although there are several different purposeful
sampling strategies, criterion sampling appears to be used most commonly
in implementation research. However, combining sampling strategies may
be more appropriate to the aims of implementation research and more
consistent wit h recent developments in quantitative methods. This paper
reviews the principles and practice of purposeful sampling in
implementation research, summarizes types and categories of purposeful
sampling strategies and provides a set of recommendations for use of
single strategy or multistage strategy designs, particularly for state
implementation research.
K - Probability sampling: Probability sampling methods is the method
which includes simple random sampling, systematic, stratified sampling.
In non -probabil ity sampling the sample are selected on the basis of non -
random criteria. And not every member of the population has the
opportunity of being included. Probability sampling is also called as the
random sampling or it is also called as representative sampli ng. The
probabilities can be assigned to every unit of the population objectively.
These techniques are needed to be very much precise to defined. These are
the techniques which cannot be used for the population that is too general
category found almost ev erywhere.
For example, if our target population is defined as college student. It
means person studying at any college of the world is an element of
population.
In certain scenarios probability sampling can be done as the population is
precisely defined an d limited to an infinite number of elements.
The advantages of probability sampling techniques are that the sampling
techniques are that the sampling techniques reduces the chance of
systematic errors. This method minimizes the chance of sampling biases.
A better representative sample is produced by using probability sampling
techniques.
L -Non-probability sampling : non -probability sampling is called as
judgement or non -random sampling each and every unit of population
does not get an equal opportunity of the participation in the investigation.
These techniques need not population to be very precisely defined. Non -
probability techniques make, if possible, to take a sample of the
population elements which are in numbers.
Non-probability sample is very much suited for explore to research
intended to generate new ideas that will be systematically tested later. munotes.in
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67 Probability sampling is best option for research that is intended to develop
the under and of a population
The advantages of this techniques are that th ey need less efforts. It
requires less time to get the task complete. They are not very much
expensive.
The disadvantages of the sampling techniques are that they are systematic
error and sampling basic.
The sample cannot be claimed to be a good representa tive of the
population.
4.3.4 The main type of probability sampling are as follows .
1. Simple random sampling
2. Systematic random sampling
3. Stratified random sampling
4. Cluster sampling
5. Multistage sampling
1. Simple random sampling :
As sample size is large it shoul d choose randomly It is a type of sampling
in which each and every element must be mutually exclusive i.e., it should
be able to distinguish from one another and does not have any over
lapping characteristics.
For Example:
Suppose researcher try to select a simple random sample of 100 students
from a college. Researcher will assign a number to every student in the
college database from 1 to 200 and use a random number generator to
select a sample of 100 numbers.
2. Systematic random sampling
In this type of sa mpling is also used in homogeneous population it means
selection is done from the targeted sample this method is bit different from
random sampling.
In such kind of sampling the elements are selected on the regular intervals.
The interval may be in terms o f time space or order. The list of elements
may or may not be required before taking the research or before
conducting it .
Thus, this regularity and uniformity in selection makes the sampling
systematic. It is calculated by dividing the total population size by the
desired population size.
Example:
Suppose the names of 200 students of a university are sorted in the reverse
alphabetical order. To select a sample in a systematic sampling method,
we have to choose some 25 students by randomly selecting a sta rting munotes.in
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68 number, say 5. From number 5 onwards, will select every 15th person
from the sorted list. Finally, we can end up with a sample of some
students.
3. Stratified random sampling
This type of sampling method is used when population is heterogeneous
i.e., every element of population that does not matches all the
characteristics of predefined criteriaInstead of element differ from one
another on characteristics.
The sub groups are formed they are called as single stratum. The topic and
nature of the investiga tion tells on what criteria the strata are to be made.
This formation of strata can also be called a mini reproduction of
population as each stratum consist of elements that are different from
other element in some characteristics.
For the investigation th e young adults are taken in account, so this
population may need to be divided into sub groups like male young adults
and female young adults, educated young adults etc. in this way each
stratum is a different population.
There are basically two techniques that are used to allocate sample from
strata a proportional allocation technique the sample size of a stratum is
made proportional to the number of elements in each of stratum.
For example, there are four bags (A, B C and D), each with different balls.
Bag A has 50 balls, bag B has 100 balls, bag C has 150 balls and D has
200 balls. We have to choose a sample of balls from each bag
proportionally. Suppose 5 balls from bag A, 10 balls from bag B ,20 balls
from bag C and 25 balls from D.
4. Cluster sampling
Cluster sampling is the group of elements residing in one geographical
region is called as cluster. And sampling of clusters is also known as
cluster sampling. This sampling is techniques is used when the elements of
the population which are spread over a wide geographical area.
The population is divided into sub groups called as clusters on the basis of
their geographical allocation. Usually, this division of population is
similar to what the standard of division has been used get.
The clusters ought to be homogenous among them on the characteristic’s
variable of the research.
5) Multistage sampling
It is a sampling technique where two or more probability technique are
combined it is also used when the elements of population are spread over a
wide geographi cal region and it is not possible to obtain a representative
sample with only one a for mentioned technique. munotes.in
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69 It can be described as sampling within the sample.
Probability sampling vs Non -probability Sampling Methods
4.3.5 Differences between probability sampling methods and non -
probability sampling methods. Probability Sampling Methods Non-probability Sampling Methods It is a sampling technique in which
samples taken from a larger population are
chosen based on probability theory. It is a technique in wh ich the
researcher chooses samples based on
subjective judgment, preferably
random selection. These are also called as Random sampling
methods. These are also known as non -random
sampling methods. These are used for research which is
conclusive. These ar e used for research which is
exploratory. This method takes long time to get the
data. This method is easy to collect the data
quickly. There is an underlying hypothesis in
probability sampling before the research
work starts and objective of this method is
to validate the defined hypothesis. The hypothesis is derived later by
conducting the research study in the
case of non -probability sampling.
4.3.6 Essentials of good sampling
1. To obtain reliable information about the population.
2. To test the reli ability and validity of difference between the sample
estimates and population parameters
3. Representativeness –Researcher must select the sample in a manner
which represents the universe in its truest sense. Further, if you fail to do
so, then you migh t get misleading results.
4. Adequacy – Researcher should also select the size of the sample
adequately which represents the parametric characteristics of the
population.
5. Homogeneity – This is another important element of a sample
investigation . Homogen eity means that there is no basic difference in
the nature of the units in the sample and the universe. munotes.in
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70 In order to take a right conclusion, the sample must possess the following
essential characteristics.
1. Representative
The sample should truly present th e features of the verse. For this
investigator should be free from bias and the method of collection should
be free from bias and the method of collection should be appropriate. All
the samples which are selected should be true then only the results will b e
reliable otherwise it will be misleading. Random method of selection
should be used to ensure representativeness.
2. Adequacy
Adequacy is very much essentials for good sampling the size of the
sample should be adequate that is should not be too big not smal l but
adequate with the size of the population. All the size should be adequate or
the results will not be accurate in the nature. In order to have exact result
all the sample should be moderate.
3. Homogeneity
There should be homogeneity in the nature of all the units selects for the
sample. Theunits of the sample one of the heterogeneous. Character it will
impossible to make a comparative study with them.
4. Independent ability
The method of selection of the sample. Should be such that the items of
the sample are selected in an independent manner. This means that
selection of one item should not influencers. The selection of another item
in any manner a that each item should be selected on the basis of its own
merit. All the items should have the equal opportu nity of being selected.
This influences the probability of selection.
Sampling is done to understand the consumer wants and what satisfy them
hence researcher collects lots of sample from market to collect the
information.
Sample selected should be the rep resentative of the whole population and
it can be obtained through the random sampling. Size of sample should
also be adequate. More the size of sample more the result will be perfect.
All the units should get the chance of getting selected decision should not
be bias or judgmental. There should not be any discrimination in the units
all the units in the whole universe should get the equal opportunity.
The advantages of essential sampling are that they are not time consuming
as it considers only the selecte d area of population. It is inexpensive in
nature as their limited number of respondents. With the help of good
sampling the result of the sample study might be more accurate as it
considers smaller units so it helps them to study the whole thing in detail .
Because of that result is more accurate in nature. In order to get more
detailed and reliable information respondent need to be interviewed. For
some specific studies only sample method also can be used. munotes.in
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71 If the number of populations is greater in the siz e and the size of sample
should also be greater. If the money and the time are limited then the
research should be done by taking the smaller portion. If one needs the
higher accuracy large number of samples should be taken small units may
not be sufficien t. If the samples are the random samples, then the size
required for the sampling is large. On the other hand, one is using
stratified random sample then the small size is also sufficient. For the
detailed study of the unit small size is usually convenient .
Using the sampling method in the research samples helps to save the
money and time. It is most suitable strategy which can be used to gather
the accurate information.
Every researcher knows the important of essentials of sampling in the
research projects as helps to know through limited sources of resources.
Samples helps to gather accurate information it just that it should be
representative, adequate, reliable and it should have independent ability.
4.4 SUMMARY
Sampling is a process which is used in the analysis of states in which
number of observations are taken from the larger group such as
population. The method of the sample of larger population upon the
sample of larger population and analysis which is to be done. Most
commonly sampling method inclu des random sampling or systematic
sampling. Basically, sampling is used in the selection of a group of the
population of interest in a research study. In huge research the
participation of a whole population of interest is not possible, so a smaller
group depends upon for a collection.
Sampling helps in taking a portion of few materials or protect to test
chemical analysis the main purpose of quality control and identification.
Sampling usually gives permission to researchers to obtain sufficient date
a to answer the research question.
The sampling generally describes the minimum sampling rate at which a
continuous time signal needs to be uniformly sampled so that the original
signal can be completely recovered
Asample is defined as a smaller set of data t hat a researcher chooses or
selects from a larger population by using a pre -defined selection method.
Sampling is basically the selection of the subset of individual units from a
wide group such as population to estimate feature of the entire population.
Statisticians usually try to collect samples that represents the population in
questions. Sampling helps to reduce cost and increase data collection that
measuring the whole population that can provide in cases where it’s not
possible to sample whole popula tion every observation counts one more
properly. In survey sampling factors such as weights can be applied to the
data for the sample design. munotes.in
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72 Terms of sampling – Population, Sample, frame, Sample, Unit, Sample
size, Generalizing, Validity, Bias etc.
Techni ques of sampling
Simple random sampling, stratified simple random sampling, convenience
sampling, sampling systematic, quota sampling, snowball sampling,
purposive sampling, voluntary sampling, consecutivesampling, purposeful
sampling.
The method of selec tion of the sample. Should be such that the items of
the sample are selected in an independent manner. This means that
selection of one item should not influencers. The selection of another item
in any manner a that each item should be selected on the basi s of its own
merit. All the items should have the equal opportunity of being selected.
This influences the probability of selection.
Sampling is done to understand the consumer wants and what satisfy them
hence researcher collects lots of sample from marke t to collect the
information.
Sample selected should be the representative of the whole population and
it can be obtained through the random sampling. Size of sample should
also be adequate. More the size of sample more the result will be perfect.
All the units should get the chance of getting selected decision should not
be bias or judgmental. There should not be any discrimination in the units
all the units in the whole universe should get the equal opportunity.
The advantages of essential sampling are th at they are not time consuming
as it considers only the selected area of population. It is inexpensive in
nature as their limited number of respondents. With the help of good
sampling the result of the sample study might be more accurate as it
considers sm aller units so it helps them to study the whole thing in detail.
Because of that result is more accurate in nature. In order to get more
detailed and reliable information respondent need to be interviewed. For
some specific studies only sample method also can be used.
Every researcher knows the important of essentials of sampling in the
research projects as helps to know through limited sources of resources.
Samples helps to gather accurate information it just that it should be
representative, adequate, rel iable and it should have independent ability.
4.5 EXERCISE
Fill in the blanks
Fill in the blanks
1 ______________ is a probability method?
(a) Judgement (b) Quota (c) Simple random (d) Convenience
munotes.in
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73 2. Which of the following is not a type of non -probability sampling?
(a) Quota sampling (b) Convenience sampling (c) Snowball sampling
(d) Stratified random sampling
3. Sample is regarded as a subset of?
(a) Data (b) Set (c) Distribution (d) Population
4. Among these, which sampling is based on equal probability?
(a) Simple random sampling (b) Stratified random sampling
(c) Systematic sampling (d) Probability sampling
5. Wrong questionnaire is an example of __________
(a) Primary data collection problem (b) Secondary collection probl em
(c) a and b both (d) None of the above
6. Questionnaire is filled by ……………….
(a) Respondent (b) Everybody (c) Enumerator (d) None of the above
7. Identifying causes of a problem and possible solution to a problem is
(a) Field Study (b) Diagnosis tic s tudy (c) Action study (d) Pilot study
8. A formal document that presents the research objectives, design of
achieving these objectives, and the expected outcomes/deliverables of
the study is called
(a) Research design (b) Research proposal (c) Research hy pothesis
(d) Research report
9. Which technique is generally followed when the population is finite?
(a) Systematic Sampling Technique (b) Purposive Sampling Technique
(c) Area Sampling Technique (d) None of the above
10. Cluster sampling, st ratified sampling and systematic sampling are
types of __________
(a) Direct sampling (b) Indirect sampling (c) Random sampling
(d) Non-random sampling
11. _______research is based on the measurement of quantity or amount.
(a) Qualitative (b) Descriptive (c) Quantitative (d) Numerical
12. In the _______research, the researcher has to use facts or information
already available .
(a) Analytical (b) Descriptive (c) Applied (d) Distinctive munotes.in
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74 13._____ research is concerned with qualitative phenomena.
(a) Qualitati ve (b) Descriptive (c) Quantitative (d) Numerical
14. ______ is data -based, coming up with conclusions that are capable of
being verified, by observation or by experiment.
(a) Contextual research (b) Conceptual research (c) Ideal research
(d) Empirical research
15. A ________ refers to some difficulty that a researcher experiences in
either a theoretical or practical situation
(a) Research hypothesis (b) Research experience
(c) Research pro blem (d) Research crisis
16. _______ as a testable statement of a potential relationship between two
or more variables.
(a) Research hypothesis (b) Research experience
(c) Research problem (d) Research cri sis
17. Research design is a _________for conducting the marketing research
project
(a) strategy (b) framework (c) blueprint (d) both B & C
True or False
1. Quantitative data is data in the form of numbers
True
2. Positivist prefer qualitative data
False
3. Stratified random sampling is where we choose participants as they are
easy to access
False
4. Questionnaires are time consuming and expensive
False
5. Unstructured interviews are time consuming
True
6. Unstructured interviews are not flexible
False
7. Questionnaire mode of approach is qualitative research
False munotes.in
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75 8. Surveys and questionnaires are primarily used for collecting
information from a largenumber of users.
True
9. Sample is a representative unit of the population
True
10. Research can never b e without any non -sampling errors, but sampling
errors can always be avoided.
False
11. The final product of all the research activity is the report
True
12. Design of research must be a blueprin t for the general collection
True
13. The method of selection of sample should be such that items of sample
are selected in dependent manner.
True
14. Every researcher knows importance of essential sampling.
True
15. Using the sampling method in the research samples helps to save the
money and time
True
16. Purposeful sampling is widely used in qualitative research
True
17. A sample is defined as a larger set of data
False
Match the following
1 Design of Research a) qualitative research
2 Purposeful sampling b) Bluepr int
3 sampling method c) Samples taken from a larger
population
4Final Product of the Research d) save the money and time
5Probability Samling e) Report
Answers: 1 -B 2 -A 3 - D 4-E 5 -C munotes.in
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76 Shorts Notes
Purposeful sampling – Sampling - Voluntary sampling - Snowball
sampling - Population - Snowball Sampling - Cluster sampling -
Multistage sampling
Answers the following
1. Write techniques of sampling.
2. What are essentials of good sampling?
3. Write differences between probability sampling methods and non -
probability sampling methods
4. Differences between probability sampling methods and non -
probability sampling methods.
18. Explain the phases of Research design
19. Explain the Concept and techniques of sampling
20. Discuss the various type of probability sampling
8 Advantages and Disadvantages of quota sampling
4.6 REFERENCES
https://www.bing.com/search?q=questionnaire
https://ww w.bing.com/search?q=sample+questions+on+research+design
https://www.bing.com/search?q=research+design+meaning
Below is the list of marketing research books recommended by the top
university in India.
Boyd, Harper W. Jr., Westfall, Ralph and Stasch, Stanle y, Marketing
Research: Text and Cases, Richard D. Irwin Inc., Homewood, Illinois.
Green, P. E. and Tull, D. S., Research for Marketing Decisions, 5th
edition, Prentice -Hall of India, New Delhi.
Luck D. J., Wales, H.G., Taylor, D. A. and Rubin R. S., Market ing
Research, 7th Edition, Prentice -Hall of India, New Delhi.
Tull, D. S. and Hawkins D. I., Marketing Research : Measurement and
Method, 6th Edition, Prentice -Hall of India, New Delhi.
munotes.in
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77 5
DATA COLLECTION - I
Unit Structure:
5.1. Objective
5.2. Introduction
5.3. Primary data
5.4. Secondary Data
5.5. Summery
5.6. Exercise
5.7. References
5.1. OBJECTIVE :
i. To understand the concept of data collection.
ii. To explain the various data coll ection methods used in research.
iii. To comprehend the primary data concept.
iv. To comprehend the secondary data concept.
5.2. INTRODUCTION:
According to the research design, the researchers must collect all relevant
information about his research probl em from different sources.
Researcher can carry out by using both primary and secondary data. The
data serve as the base material for analysis. Without an analysis of factual
data, no specific conclusions can be drawn on the questions. The
relevance, adequ acy and reliability of data determine the quality of the
findings of a study. While collecting data researchers must ensure that the
information collected is relevant and unbiased. The data must be complete
in every way and it must be relevant to the resea rch problem. This chapter
deals with data collection process for the same.
5.3. PRIMARY DATA:
The collection of data is very crucial in statistical analysis. The method of
collecting data is divided into two categoriesi.e., primary and secondary
data. The primary data in this process is data that is being collected for the
first time, whereas the secondary data is data that has already been
collected by others. munotes.in
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78 The term "primary data" refers to data that has never been used before.
Relevant respondents are surveyed for primary data and data can be
collected in a variety of ways, including surveys, observational
experiments and so on. Before conclusions primary data must be
processed and analysed. Data form the basis for testing the hypothesis
formulated in a study. For performing research on the literacy level, the
primary and secondary sources of data can be used very effectively.
5.3.1. Definition and concept of Primary Data:
Definition:
Primary research is defined as “ a methodology that researchers use to
collect data directly rather than relying on data from previous
studies .”
Primary data is information gathered for the first time, usually through
personal experiences or evidence and is used in research. It's also known
as unprocessed data or first -hand data. Primary research is conducted
exclusively to address a specific problem that needs in -depth
interpretation. In case of primary data researcher is technically "owner" of
the data.
5.3.2. Meritsof Primary Data :
i. More authentic:
Researchers conduct primary data research and development by giving
personal attention to each of the questions they wish to survey.
Researchers more often rely on primary data they collected than relying on
secondary sources or other's data. As a result, data becomes more r eliable
and accurate. It can be more trustworthy than secondary data.
ii. Collection of relevant data
The primary data which is generated is first -hand data. No one else's data
has been used to develop primary data that keeps the data relevant and
people rely on such data that is more updated. Primary data is typically
collected through a questionnaire or personal contact, ensuring that the
data collected is accurate and relevant.
iii. Greater data control :
The researcher, conducting the survey can manage the dat a through
questionnaires or other methods, because he has complete control over the
primary data. To make the data more relevant, researcher can modify or
make changes to it. The researchers may also have difficulty in collection
of primary data because th e target group may not easily understand the
purpose of the survey therefore a little modification can help them obtain
accurate data.
iv. Data privacy is protected :
The researchers who conduct survey work also ensures data
confidentiality. When a small grou p of people is in charge of the entire munotes.in
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Data collection - I
79 survey there is a high level of secrecy among them. Furthermore, the
feedback they receive are always private to researchers.
v. The targeted problem is addressed :
Data collectors prepare questionnaires and conduct int erviews with the
targeted group to obtain information. Also, the issue is addressed so that it
can be brought to light and settled after receiving proper responses. In this
way, the research can be made more constructive and difficulties can be
dealt with more easily.
vi. Primary data is easier to process:
Primary data collected through various methods is made simple and easy
to understand so that anyone interested in data can understand it at a quick
look. It's also more effective if the feedback researcher collected is
accurate and reliable.
vii. Data is easier to understand :
Primary data collected through various designs and methods is simple and
easy to understand so that anyone interested in data can understand it at a
glance. It's also more effective for t he feedback as researcher get it
accurate and reliable.
viii. Others can use it as secondary data :
Researcher benefited from the data as he collected as a primary data, but it
also helps other researchers as secondary data.
ix. Specific and particular :
The most important part of primary data is it caters to the requirement of
specific purpose. Since secondary data is collected and stored for someone
else’s requirement and filtering it for a particular objective would be
difficult.
x. Flexible nature:
It is possi ble to record the transformation of a situation over time. As a
result, primary data is flexible, which is beneficial to researchers. Data can
be modified to fit the current situation and futuristic perspectives can be
included. As a result of the findings a better data collection method will be
developed.
5.3.3 Demerits of Primary Data :
i. Costly data :
Compared to secondary data, primary data collection methods are more
costly. It needs the hiring and training of personnel to collect data through
interview s, surveys and observation. Experiments must also be conducted
with specialized technology. Researchers are required to travel and use
expensive equipment. Also, after receiving feedback, proper
documentation is required which is time -consuming and expensi ve to
maintain. When a researcher uses secondary data however, such costs are
not necessary. munotes.in
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80 ii. Time -consuming data:
Collecting data from primary sources takes time because it takes time to
collect information from each respondent, observe the sample and con duct
an experiment. Because it takes time, it can cause a delay in addressing the
issue. If researchers use secondary data to gather information from other
sources it will saves time of researcher.
iii. Required more workforce :
More workforce is required in t he case of primary data because only one
person cannot conduct a survey or collect primary data on their own.
Furthermore, the number of personals required is greater and they must be
paid after their work is completed.
iv. The questionnaire must be simple an d easy to understand:
Only if the questionnaire is simple and easy to understand then only the
researchers will receive accurate and valid feedback. If the researchers do
not create a set of sample questionnaires in such a way or technique that
allows peop le to easily interpret them, the feedback produced will be
incorrect or inaccurate.
v. Bias collection of data :
Due to the researcher's or respondent's biases the authenticity of primary
data may be affected. Respondents may give the researcher incorrect
information about serious subjects. It's also possible that the researcher did
not make sufficient efforts to obtain data from respondents. It may be
produced biased primary data.
vi. Data processing :
The data collected from respondents must be edited, coded, classified and
tabulated before analysis. Only after the data has been properly analysed
can useful. Data processing is very complex work in case of primary data.
vii. Sampling Error :
It is possible that information from all of the universe respondents wil l not
be possible to collect. The researcher may be required to collect data from
a sample i.e., a subset of the population. However, sample selection could
be incorrect, resulting in the collection of incorrect data and incorrect
conclusions.
viii. Experts req uired for the interpretation:
Only an expert can make the entire research meaningful by providing
genuine facts and information, so the method for collecting data, technique
and analysis must all be done by an expert.
ix. Difficult to administer :
Despite the fact that it is first -hand data collected by the researcher, the
primary data has the drawback of being complicated to administrate. In the
case of data collection via questionnaire, respondents frequently either do
not respond all of the questions or ans wer them in poor handwriting. It is
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81
5.3.4. Methods of Collecting Primary Data :
There are various methods of data collection. A method id different from a
tool. While a method refers to the way or mode of gathering data, a tool is
an instrument used for the method. Researchers collect primary data
directly by interacting with or observing respondent. Primary data can be
collected using a variety of methods like surveys, interviews, observati on
and experimentation etc. they are discussed below.
A. Survey Method :
The survey method is a data collection technique that involves asking
questions to respondent who are believed to have the information needed.
This data is comprehensive information a bout a particular topic collected
from a targeted group in order to conduct research. A census or a sample
survey are two types of surveys.
Census : When conducting a census, the entire universe is contacted
to gather data.
Sample Survey : In a sample surv ey, data is collected from a subset of the
universe's respondents.
Methods of Survey:
The researcher can use various survey methods depending on the research
problem, i.e., the number of respondents from whom data must be
collected, the time available to t he researcher and his budget constraints
etc. The following are various survey methods.
i. Interview :
In this method, the researcher needs to meet the respondents in person and
asks them questions about his research problem and gathers relevant data.
This method of data collection is the most traditional, expensive and but
effective.
ii. Telephonic Survey:
This method does not require the researcher to meet with respondents in
person. The survey on the other hand is conducted over the phone. On the
phone, th e researcher asks the respondents a series of questions in order to
gather the necessary data.
iii. Mail Survey:
This method of survey is commonly used when the number of respondents
are large and the researcher faces a geographic challenge. In this method, a
questionnaire is created and mailed to respondents or it can be advertised
in newspapers and magazines and respondents are asked to complete the
questionnaire and return it to the researcher.
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82 iv. Online Surveys:
This method of collecting information is growi ng rapidly these days, due
to high penetration of internet access. In this method, the researcher can
collect information from respondents by sending a Google Form or
Microsoft Form via email or other communication applications such as
WhatsApp or telegram etc.
v. Pilot Survey :
It is survey on small scale. Every research project costs money, time and
effort, therefore conducting pilot study prior to beginning the process will
be extremely beneficial, especially when a large number of sample
size involved. Su rvey testing takes a long time and requires a lot of
resources. A pilot survey is a technique for evaluating or testing a
questionnaire with a smaller sample size than the intended sample size.
A small group of sample population can help researcher to impr ove
research quality.
It provides the information on the following aspects.
a. It enables the researcher to have proper knowledge of the universe to
be sampled.
b. The adequacy of the sample design for survey.
c. It also tests the efficiency of briefing provid e to staff
d. It also provides the probable test of the main survey to be conducted.
B. Interview Method :
In an interview method, the researcher needs to meet the respondent and
interacts with him or her individually. The researcher and the respondent
interact with each other face to face in this method. It's also known as a
one-on-one interview. In this method, the interviewer asks the respondent
questions and collects data from the responses.
Following are the variety of formats of interviews.
i. Structure d Interview :
The interviewer uses a set of predetermined questions and highly
standardised recording techniques in this type of interview. Closed -ended
questions or questions that respondents can answer with "yes" or "no" are
common in structured intervie ws. The interviewer usually asks each
interviewee the same questions in the same order. Structured interviews
can often be completed quickly because they follow a standard format that
is easy to recreate.
ii. Unstructured Interview :
In this method, the inte rviewer does not use a system of predetermined
questions or standardised techniques for recording information, instead
depend on entirely on flexibility and criteria. An unstructured
interview also known as an informal interview. In unstructured interviews ,
the interviewer does not ask each interviewee the same set of questions.
Unstructured interviews, on the other hand, rely on open -ended questions.
The interviewer can ask follow -up questions and allow interviewees to munotes.in
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83 elaborate on their responses in unstr uctured interviews. As a result, an
unstructured interview characterizes a natural conversation.
iii. Clinical Interview :
This type of interview focuses on a person's broad underlying feelings or
motivations as well as the course of their life.
iv. Non-directiv e Interview :
In this type of interview, the interviewer simply encourages the respondent
to talk about the topic with as little direct questioning as possible.
v. Focused Interview :
Conducting a focus group interview which involves interviewing a group
of respondents at the same time is a popular research interview method.
Focus group moderators usually encourage respondents to respond with
each other while also observing the group to gain an understanding of real
perceptions. Respondents in focus groups a re more likely to respond
spontaneously and confidently than in other interview settings because the
group setting feels more realistic. In this type of interview, the
interviewer's goal is to keep the respondent focused on a specific
experience and its co nsequences.
vi. Interview in person :
A personal interview is a one -on-one interaction between an interviewer
and an interviewee that takes place in person. If researcher wants to
respond directly to respondent and customize questions to them, personal
interviews are suitable. Also, researcher can ask follow -up questions to
produce more information. Personal interviews typically have higher
response rates than other interview methods, making them ideal for
gathering large amounts of precise data.
vii. Online co nversation :
Another type of research interview is an online interview. Surveys or
video chat applications can be used in online interviews. These days,
video conferencing platforms like Zoom, Google Meet and Microsoft
Teams can be used to conduct such in terviews. Interviewers and
interviewees do not have to be in the same place at the same time when
using this method. This can help researcher to quick collection of data
from a large number of people.
C. Observation Method :
This is altogether a different method of collecting data in which the
researcher does not ask the respondent any questions but instead observes
their behavioural patterns. Observation is defined as "Observation is a
technique that involves systematically selecting, watching, listening,
reading, touching and recording behaviour and characteristics of living
beings, objects or phenomena ."
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84 Types of Observations :
i. Structured Observations :
Structured observations are most commonly used in studies that are
intended to describe a problem or test a causal hypothesis. Structured
observation procedures assume that the researcher understands which
aspects of the problem under investigation are relevant to his research
goals and is thus able to plan the recording of observations before
beginning d ata collection.
ii. Unstructured Observations :
In practice, it is rarely possible to plan out the 'observation' process long in
advance. The researcher may not have enough hints to structure his
observations, which may require changes in what he observes, es pecially
in exploratory studies. The unstructured observations are flexible, changes
in the focus can be made as needed if and can be justify it.
iii. Participative Observation :
Participant observation is an attempt to bring the observer and the
observed clo ser together by making the observer a member of the group,
allowing him to experience what they do and work within their
framework. The researcher, in particular, becomes a member of the
community he is studying. In participative observation natural behavi our
of group is recorded and truth of information can be assessed. But in
participative observation researcher may lose the objectivity with
emotional participation with the group due to alertness of group.
iv. Non-participant Observations :
Non-participan t observation, is the observer's lack of involvement in the
life of the group that the researcher is studying. In other words, in non -
participant observations, the observer plays a disconnected role and collect
data without making any effort to connect wit h the group under
observation.
D. Experimentation Method :
In the field of science, the experimentation method of data collection is
commonly used. Through experiments, this method of research, researcher
investigates the cause -and-effect relationship betw een two or more
variables. An experiment is a well -structured study in which researchers
try to figure out causes, effects and processes are involved in specific
research. The researcher usually controls this data collection method,
deciding which subjects are used, how they are grouped and how they are
treated.
An experiment is a data collection method in which researcher change
some independent variables and observe their effects on dependent
variables. Independent variables are those that researcher can manipulate,
while dependent variables are those that change as a result of
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85 The most significant benefit of conducting an experiment is that it allows
researcher to investigate causal relationships that an observational study
cannot. Experime ntal research can also be applied to a variety of
fields including medical research, agriculture, sociology and psychology.
Experiments, also have the disadvantage of being costly and time -
consuming.
E. Schedules :
While collecting data from interviews or observations, the researcher may
use a schedule. A schedule is a tool for gathering information from
respondents. Questions and statements are included in the schedule. It
provides respondents with blank spaces or tables to fill in their responses.
The sch edule is important because it serves rationality by informing the
researcher of the various aspects to be observed.
Following are various types of schedules.
i. Rating Schedules:
A rating schedule is a list of positive and negative statements about a
concep t. Respondents are asked to share their opinion, preferences and
other feelings about the topic under study and a schedule is used to keep
track of their responses.
ii. Documents Schedules:
These are used to gather data and information from recorded evidence.
iii. Survey Schedules:
Survey schedules are similar to questionnaires in that they are a list of
questions that respondents must answer.
iv. Observation Schedules:
When using the observational method of data collection, observation
schedules are used.
5.4. SECO NDARY DATA
Researchers can access secondary data easily. It can be found in
newspapers, magazines, research journals and research papers etc. In
general, any researcher tries to collect data from secondary source first and
if secondary data is insufficien t or useless the researcher attempt to collect
primary data.
Secondary data is used in research to increase the sample size as well as
for the speed and consistency that comes with working with an existing
resource. Secondary data is useful in large resear ch projects where
multiple research teams are collecting secondary data together. After that,
the principal investigator can focus on primary research or specific areas
of interest. This division of work allows researchers to learn more in less
time. A res earcher may have gathered data for a specific project and then
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86 the data may have been collected for general use rather than for specific
research purposes.
5.4.1 Definition and con cept of secondary data:
Secondary data is information that has already been compiled from
primary sources and made accessible to other researchers for their own
research. It is a type of information that has already been compiled.
"Data collected by part y other than the researcher is referred to as
secondary data."
Data from secondary sources has already been gathered. As a result, it's
possible that it's less reliable than primary data. When investigation time is
limited and the accuracy of the research can be determined to some
extentsecondary data is typically used.
5.4.2 Merits of Secondary Data :
The following are some of the benefits of secondary data.
i. Secondary data is easily accessible:
Secondary data is collected from both published and unpublish ed sources.
Internal or external sources provides secondary data. Other researchers
have already collected, processedand published it.
ii. Convenient to collect:
Due to readily availability of secondary data, it is simple to collect. In
comparison to primary data secondary data is much easier to collect.
iii. Less time and money consuming :
Secondary data is simple to collect because it is readily available, so it can
be done in less time. Collecting secondary data is also less expensive. The
majority of secondar y sources are either free or very inexpensive to use. It
not only saves researchers money but it also saves time.
iv. Quantitative data is provided by secondary data :
The amount of information available through secondary data is enormous.
Almost all subjects have secondary data available.
v. Significance:
For almost all subjects, secondary data can be found. But even so,
secondary data may or may not be related to the research topic, therefore
researcher must assess and process the available secondary data.
vi. Less Data Processing :
Secondary data has already been processed; this requires less data
processing. It is simple for researchers to use secondary data in their
studies.
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87 vii. Economical :
Collecting secondary data is economical. The researcher has access to
secondary data via internal or secondary sources. The researcher does not
need to hire or staff to collect data, conduct surveys or experiments. Thus,
secondary data is economical in its nature.
viii. Supplementary to primary data :
Secondary data is informat ion gathered and processed by other researchers
for a different purpose therefore it may or may not be completely relevant
to the research problem. But secondary data can be used to supplement
primary data in this situation.
viii. Time saving :
Secondary data is readily available to the researcher through a variety of
internal and external sources; therefore, the researcher can collect
secondary data quickly and efficiently.
ix. No sampling errors :
Because there is no need for sampling when collectingsecondary da ta,
there is no risk of sampling error in secondary data.
5.4.3. Demerits of Secondary Data :
i. Inappropriate :
Secondary data may or may not be appropriate for all types of research.
Secondary data is insufficient and the researcher must collect primary dat a
in order to solve the research problem. Secondary data isn't collected to
the researcher's needs because it was gathered for a different purpose in
the past as per his/her objectives. As a result, secondary data may be
unreliable for researchers’ require ments. Secondary data sources can
provide a lot of information but quantity does not always imply suitability.
ii. Correctness :
Secondary data isn't always reliable. Secondary data available to
researchers may not be authentic, resulting in poor secondary d ata quality.
When choosing secondary data to use in his research the researcher must
be cautious.
iii. Irrelevant Data :
Secondary data is information gathered by another researcher for a
different research project. Therefore, secondary data as mentioned abo ve
may or may not be relevant to the research.
iv. Biased Data :
The quality of secondary data is beyond the researcher's control.
Secondary data may be contaminated by the researcher's and respondents'
biases at the time it was collected. Secondary data is typically biased in
favour of the researcher who collected it because it was collected by
someone other than researcher. This may not meet researchers’
requirements.
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88 v. Appropriateness :
The secondary data that is available may not be sufficient for the
researcher. Secondary data is publicly available information that was not
gathered specifically for the purpose of research problem. In this case, the
researcher cannot rely solely on secondary data, he must also collect
primary data.
vi. Data quality is uncertai n:
Secondary data may be of poor quality. The information's source may be
questionable, especially if it was collectedfrom the internet. If researcher
is using secondary data to make data -driven decisions, then
researcher need to assess the information's reliability by learning how it
was gathered and examined.
vii. Not timely:
Secondary data were collected in the past, so it may be out of date. Many
variables and their values get change over the period of time. This
problem can be critical in a number of co ntexts of research.
viii. Inaccurate Information :
Some of the data sources are out of date and no new data is available to
replace them. The national census for example is not usually updated on a
yearly basis.
ix. No control over data and validity :
Secondar y data isn't usually collected specifically for researchers. Instead,
many businesses and individuals can access it for free or for a small fee.
So, for researcher this isn't exactly a significant advantage. It is due to,
secondary data is in controlled b y others.
5.4.4. Sources of Secondary data :
Books, personal sources, journals, newspapers, websites, and government
records are all examples of secondary data sources. When compared to
primary data, secondary data is known to be more easily accessible. If
researchers use these resources, then they require very little research and
workforce too.
A. Major sources of secondary data can be classified are as follows:
i. Published sources :
The majority of secondary data is obtained from published sources. Th e
following are a few major sources of published information :
Official statements and publications of governments
Statistical synopses, census records and other reports issued by various
government agencies
Publications and reports from chambers of comme rce, financial
institutions, trade associations and other institutions
Magazines, journals and periodicals munotes.in
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89 Publications from government agencies such as the Central Statistical
Organization (CSO) and the National Sample Survey Organization
(NSSO)
Report s from research scholars, bureaus, economists and other experts.
ii. Unpublished sources :
Statistical data can also be found in a number of unpublished sources. In
comparison to published sources, this may not be readily available and
accessible. They are on ly accessible if the researcher shares them with
another researcher who is not permitted to reveal them with anyone else.
The following are some of the major unpublished sources from which
secondary data can be collected.
The records kept by individual and commercial enterprises
The research conducted by teachers, professors and professionals
Statistical data compiled by various departments and agencies of the
federal and state governments, as well as undertakings, corporations
and other entities.
iii. Interna l Sources :
Internal sources refer to data available within the organisation through its
own records. An organisation generates huge data which could be useful
for decision making. Various internal sources of secondary data are
purchase and sales record s, financial statements etc.
iv. External Sources :
External sources of secondary data include information collected from
various published sources such as books, magazines, newspapers reports,
research paper online sources etc. Like government publications , private
organisations and general publications etc.
B. Broad classification of sources of secondary data
i. Books :
Books are one of the oldest methods of data collection. Books on almost
any subject are now available. When conducting research, research ers
must first search for books on the subject and then select books from the
library's collection in that subject area. If researchers are carefully chosen
as an authentic source of authentic data, books can be useful in preparing a
literature review.
ii. Published Sources :
There are numerous published resources available for a variety of research
topics. The uniqueness of the data obtained from these sources of
information is largely determined by the author and publication company.
Published sources can b e printed or electronic, depending on the situation.
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90 iii. Journal :
Journals are gradually becoming more important than other books when it
comes to data collection. This is due to the fact that journals are updated
on a regular basis as new published articl es are providing current and
relevant information. Journals are usually more specific than research
papers.
iv. Newspapers :
In most situations, data obtained from a newspaper is extremely
trustworthy. As a result, it is one of the most reliable sources of s econdary
data. But newspapers typically publish data that is more political,
economic and educational than scientific. As a result, newspapers might
not be the best source of scientific information.
v. Websites :
The information shared on websites is ge nerally unregulated and as a
result it is less trustworthy than information obtained from other sources.
There are, however, some regulated websites that only share authentic data
and can be relied upon. The majority of these websites are paid data
collect ors either government or private.
v. Blogs :
Blogs are one of the most popular online data sources and they may be
less reliable than websites. Almost everyone has a blog these days and
many people use them to earn money through paid advertisements. As a
result they can't be trusted all of the time.
vi. Government Documents :
Government records are a valuable and reliable secondary data source.
They include data that can be used in marketing, management,
humanities and social science studies.
Census data, he alth records, education institute records and so on are
examples of these records. They're usually gathered to help with proper
planning, budgeting and project prioritization.
vii. Podcasts :
Podcasts are gradually becoming more popular and many people listen to
them instead of listening to the radio. They function similarly to online
radio stations and are gaining in popularity. During podcasts, data is
commonly shared and listeners can use it to collect data.
viii. Other sources of secondary data :
• Letters
• Public radio stations
• Records from the public sector
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91 5.5. SUMMARY
In this chapter we have learnt about the various methods of data
collection. The research process has been thoroughly discussed in this unit
as well as primary data, its features, advanta ges and disadvantages. Data
collected about situation, phenomenon issue or group of people can come
from either primary sources or secondary sources. This topic also goes
over multiple methods used to collect primary data in depth along with its
limitation s. Even so, a researcher may be required to use secondary data in
addition to primary data.
Data that is classified as secondary in one study may be considered
primary in another. When data is reused, it becomes primary data for the
first research and sec ondary data for the second research. Primary and
secondary data has flaws that may negatively impact the research's
outcome, but also has their own some advantages. It all depends on the
circumstances, the researcher, and the type of research being conduct ed.
5.6. EXERCISE
Q. 1 . Fill in the blanks :
i. Primary data is information gathered for the …………time.
( First , second, third, many)
ii. In case of primary data researcher is technically ………… of the
data.
( Owner , borrower, customer, buyer)
iii. in ………. metho d the researcher needs to meet the respondents in
person. ( Interview, Telephonic Survey, Mail Survey, Online Surveys )
iv. The interviewer uses a set of predetermined questions and highly
standardised recording techniques …………type of interview.
(Structured In terview , Unstructured Interview, Clinical Interview,
Non-directive Interview )
v. …………….is a technique that involves systematically selecting,
watching, listening, reading, touching, and recording behaviour and
characteristics of living being s, objects or phenomena.
(Observation, Interview, Survey, None of the above)
vi. Through ……………. method of researcher investigates the cause -
and-effect relationship.
(Experimentation, Observation , Interview, Survey )
vii. Data collected by party other than the r esearcher is referred to as
…………data.
( Primary, secondary , Prime, First hand)
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92 viii. ………….. also provides the probable test of the main survey to be
conducted.
( Pilot Survey , Interview, Observation, )
Q.2. Match the column:
Sr. no A B
i Online Surveys Lack of involvement researcher in
group
ii Structured Interview Online data sources
iii Non-participant
observations Google Form
iv Official statements and
publications of
governments Published source of data
v Blogs Set of predetermined questions
vi Podcasts People listen to them
(Answer : i. Google Form, ii. set of predetermined questions, iii. lack of
involvement of researcher in group, iv. Published source of data, v. online
data sources, vi. people listen to them)
Q.3.True or False :
i. A metho dology that researchers use to collect data directly rather than
relying on data from previous studies is known as primary data.
ii. Secondary data also known as unprocessed data or first -hand data.
iii. Observation is a technique that involves systematically se lecting,
watching, listening, reading, touching and recording behaviour and
characteristics of living beings, objects or phenomena.
iv. In an interview method, the researcher needs to meet the respondent
and interacts with him or her individually.
v. In non -participative observation the researcher, becomes a member of
the community he is studying.
vi. In the field of science, the experimentation method of data collection is
commonly used.
vii. An observation schedule is a list of positive and negative statements
about a concept.
viii. Secondary data is information that has already been compiled from
primary sources and made accessible to other researchers for their own
research.
ix. Newspapers typically publish data that is more political, economic and
educational than scientific. munotes.in
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Data collection - I
93 (Answer : i. True, ii. False, iii.True, iv. True, v. False, vi. True, vii. False,
viii. True, ix. True)
Q.4. Write Short Notes :
i. Define primarily data and explain its concepts.
ii. Write note on Experimentation Method.
iii. Schedule method of primar y data.
iv. Schedule
v. Major sources of secondary data
Q.5. Answer in Brief :
i. Explain the merits of primary data.
ii. Explain the demerits / limitations of primary data.
iii. Explain methods of survey.
iv. Which are the formats of interviews ?
v. Explain observa tion method primary data collection.
vi. Explain the merits of secondary data
vii. Which are the sources of secondary data.
viii. What are the demerits of secondary data?
5.7. REFERENCES :
i. Sachdeva J.K.(2011). Business Research Methodology. New Delhi:
Himalaya Publis hing House.
ii. Michael V.P.(1997). Research Methodology in Management. Delhi:
Himalaya Publishing House
iii. Ranjit Kumar (2014), Research Methodology : A step by step guide
for beginners, SAGE publication, ISBN :978 -93-515-0133 -6(PB)
iv. Dr. Mahesh K Jain (2009), Res earch Methodology and Statistical
Techniques, Shree Publishers and distributors, New Delhi , ISBN
978-81-8329 -315-0
v. https://www.formpl.us/blog/secondary -data
vi. https://www.researchgate.net/publication/12437403_Data_Collection_
Using_Handheld_Computers
vii. https://datalya.com/blog/business -statistics/traditional -methods -for-
primary -data-collection
viii. https://www.questionpro.com/blog/data -collection -methods/
ix. https://www.indeed.com/career -advice/career -development/interview -
methods -in-research
x. https://www.thefreshanswers.com/types -of-observation -methods/
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94 6
DATA COLLECTION – II
Unit Structure
6.1. Objective
6.2. Introduction
6.3. Qualitative Research and Quantitative Research
6.4. Quantitative Research
6.5. Qualitative Research V/S Quantitative Research
6.6. Integrating Technology in Data Collection
6.7. Summary
6.8. Exercise
6.9. References
6.1. OBJECTIVE
i. To know the concept of qualitative research.
ii. To know the concept of quantitative research.
iii. To differentiate between qualitative and quantitative research.
iv. Elaboration of integrating te chnology in data collection.
6.2. INTRODUCTION
To solve research questions researcher must collect, analyse and interpret
data when have research problem. The type of data researcher will collect
and the data collection method determined by the research problem
researcher are investigating. In this topic we will look at different types of
research methods and the benefits and drawbacks of each. Purpose of this
is topic is to give a good understanding of qualitative and quantitative
research and when to us e each of the data collection methods.
6.3. QUALITATIVE RESEARCH AND QUANTITATIVE
RESEARCH
The most generally adopted method to validate the data is the research.
There are two traditional approaches of doing research in the fields of
marketing, industr y, sociology, psychology, science & technology,
economics etc. and they are qualitative research and quantitative research.
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95 handwritten material to form conclusions, whereas quantita tive research
depends on reasoning or statistical facts. Qualitative research can be used
to learn how a person subjectively considers and interprets their social
environment. Qualitative research is exploratory and refers to factors that
can be observed b ut not tested such as language. Quantitative data is
information about quantities, and thus numbers.
6.3.1. Concept of Qualitative Research :
Qualitative research is used to get a better knowledge of human behaviour,
intentions, attitudes, experiences and other factors based on people's
observations and interpretations. It's an unstructured, exploratory method
of dealing with very complicated events that can't be explained. This type
of study is typically conducted in order to gain an in -depth understandin g
of the subject. It is done by conducting an interview with open -ended
questions, observations that are written down and so forth. Qualitative
case study is a research methodology that helps in exploration of a
phenomenon within some particular context th rough various data sources,
and it undertakes the exploration through variety of lenses in order to
reveal multiple facets of the phenomenon
When historical data is unavailable, qualitative methods are particularly
useful. And there are no numbers or math ematical calculations required.
Words, sounds, feelings, emotions, colors, and other non -quantifiable
aspects are essential to qualitative research. These methods are based on
intellect, guesswork, emotion, and other factors.
Non-numerical data, such as te xt, video, photographs or audio recordings,
is referred to as qualitative data. This type of information can be gathered
through diaries or in -depth interviews, and analysed through grounded
theory or thematic analysis. Examples of Qualitative research are Case
study, Ethnographic research, etc.
Definition :
“ Qualitative research is a type of research that focuses on gathering
information through open -ended and conversational discussion.”
Qualitative methods produce in -depth understandings of how individu als
interpret their social realities and, as a result, how they behave in that
community.
6.3.2. Features of qualitative research :
i. Based on a natural setting:
Qualitative research is frequently based on real -life situations and it is
intended to occur naturally without outside interference. They should
not be manipulated because of manipulation of qualitative research
results from research also get manipulated.
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96 ii. Adapting to the findings :
When conducting qualitative research, the researcher should ac cept the
findings that arises from research that may lead to additional research
findings.The researcher is assumed to think outside the box and track
the findings without interference.Rather than rejecting the results the
researcher should reshape and ada pt to them. This also gives the
researcher a better understanding of the problem and in some cases
aids in its resolution.
iii. Resourceful and purposeful:
Qualitative analysis is carried out on a variety of organizations,
cultures, communities, people and eve nts. The sample was chosen
because it contains a wide range of information and is regarded
as knowledgeable. The sampling is done because it provided deep
inside information about the problem.
iv. Full informative data :
Qualitative research document is kno wn to be rich in information that
provides a knowledge of the subject. Interviews and direct quotations
from respondents are examples of data collection methods that
provide direct information about respondent’s personal views and an
in-depth understandi ng of the subject matter.
v. Individual response to unique cases :
The researcher is expected to remain responsive to the results that
emerges from qualitative research rather than reframe the results. This
highlights that the results should not hampered b y any predetermined
limits because every individual response in unique in its nature.
vi. Dynamics of Research :
In most qualitative research methodologies data is collected on the
field, where the participants are encountering challenges or problems.
These are real -time data and participants are rarely required to leave
their physical areas in order to acquire data.
vii. Rather than relying on a single data source qualitative researchers
typically collect many types of data, such as interviews, observations
and records.
viii. This research technique aims to solve difficult problems by putting
them down into understandable inferences that can be read and
understood by everyone.
ix. People can create trust in the researcher because it is a more
communicative strategy and t he information acquired is raw and
unfiltered.
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97 6.3.3. Types of qualitative research methods :
Qualitative research describes either explicitly or implicitly the
purpose of the qualitative research, the role of the researcher, the
stages of research an d the method of data analysis. Accordingly, there
are wide variety of methods are common in qualitative research. The
following are the qualitative research methods that are frequently
used.
i. One-on-one interview:
Qualitative research involves direct in teraction between the researcher
and the respondent;therefore, this method is also known as
unstructured interviewing. One of the most prevalent qualitative
research methodologies is arranging in -depth interviews. It is a one -
on-one interview conducted wit h one respondent at a time. This is
purely a conversational method that allows researcher to extract more
information from the respondent. One of the benefits of this method is
that it allows the collection of exact data regarding respondent’s
beliefs and intentions. If the researcher is skilled, by using the proper
questions can fetch useful data. If further information is required, the
researchers should ask follow -up questions. In several ways, this
method differs from traditional structured interviews. Although the
researcher may have some preliminary set of questions and there are
no formal structured tools. Also, the researcher is free to change the
topic in any manner that satisfy his or her interest.
ii. Focus groups:
A focus group is another one o f the most used qualitative research
techniques for data collection. A focus group normally consists of a
small number of participants say like 6 to 10, from target sample. The
primary goal of the focus group is to obtain answers to the questions
why, what , and how.
iii. Ethnographic research:
The most comprehensive observational method for studying people in
their natural environment is ethnographic research. This strategy
requires the researchers' adaptability to the target respondents
surroundings. The pu rpose of this research is to learn about different
cultures, challenges, motivations and contexts. Ethnography is a
research method used to learn about the lives of others. It allows
researchers to understand how and why people behave in various
societies and cultures. Ethnographic research is the process of
gathering information about a group of people. It is frequently used by
anthropologists, sociologists and others who study human behaviour.
iv. Case study research:
The case study method has gained importa nce as a qualitative research
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98 This research method is used in a variety of fields, such as education
and social sciences. This method necessitates a thorough examination
and understa nding of research techniques as well as data inference. A
case study investigates a real -time phenomenon in its natural
setting with the understanding that context matters.
A case study is the best research methodology for obtaining concrete,
situational, in-depth knowledge about a specific subject. It allows
researchers to look into the case's key characteristics, definitions and
potential impact. Case studies are frequently used in a thesis or
dissertation. When researchers don't have the time or money to
conduct extensive research, they keep focused on case study.
Researcher could initiate multiple case studies to evaluate and
highlight key facets of research problem or could use just one
complex case study to explore a single subject in depth.
v. Record k eeping :
As a source of data, this strategy uses already existing trustworthy
documents and similar sources of information. This information can be
used in future studies. Therefore, one can go through books and other
reference materials to gather informat ion that will be useful in the
research.
6.4. QUANTITATIVE RESEARCH
The quantitative research approach is based on scientific methods for
collection of factual data and statistical data. It uses a variety of
mathematical and statistical methodologies to determine the cause -and-
effect relationship between two variables. This technique is also known as
"Empirical Research" since the outcomes are accurately and precisely
measured. Surveys, experiments and other methods are commonly used in
quantitative research.
Quantitative research highlights the use of mathematical tools to analyse
numerical data. The numbers in statistical analysis come from objective
measurement scales for the units of analysis known as variables. There are
four different types of meas urement scales: nominal, ordinal, ratio and
interval. Surveys can thus be used to collect data that will serve as the
foundation for clarifying a concept. Tools that require numerical inputs are
used in such surveys.
Definition :
“Quantitative research is a systemati c analysis of research problems
through the collection of measurable data and the application of statistical,
mathematical or technological methods.”
Quantitative research methods are those that use numbers as a foundation
for making broad conc lusions about a concept.
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99 6.4.1. Features of Quantitative research :
Some distinctive characteristics of quantitative research are:
i. Structured tools :
Quantitative data is collected using structured techniques such as surveys,
pre tested tools, polls and questionnaires. Structural tools help in the
collection of detailed and valid data from survey participants. Pre -testing
enables the identification of areas in the research that needs attention. It
ensures that respondents provide the predicted responses or the
researcher's purpose to fulfil the research objectives.
ii. Sample size :
Quantitative research is conducted on a large sample size that is
representative of the target data. To strengthen the study purpose,
appropriate sampling strategies must be emp loyed when generating the
sample.
iii. Closed -ended questions :
Closed ended questions, such as "yes/no" or multiple -choice questions,
require respondents to choose from a limited set of pre -defined responses.
Closed -ended questions are developed in accordanc e with the research's
goal. These questions are frequently used in quantitative research since
they assist in the collection of quantitative data.
iv. Prior research :
Before collecting data from respondents many elements connected to the
research issue are i nvestigated in prior research.
v. Simple to analyse:
Quantitative data is usually displayed in the form of tables, charts, graphs
etc. This makes it simple to analyse the data collected .
vi. Results generalisation :
The findings of this research approach ca n be applied to the entire
population in order to adopt appropriate remedial actions.
vii. Contain measurable variables :
Data collection tools include items that generates measurable study of
population. The variables of the study are measurable characteristi cs such
as age, the number of children, educational status and economic status etc.
viii. Assume a normal population distribution :
A normal population distribution curve is preferred over a non -normal
distribution for more accurate data analysis of quantitati ve data. This
usually requires a large population, the size of which is determined by the
population's characteristics. This requires the use of random sampling to
avoid researcher bias in analysing the results, which would overcome the
purpose of the stud y.
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100 ix. Present data in tables, graphs, or figures :
Tables, graphs and figures that integrate large amounts of data to show
trends, relationships and differences among variables are used to arrange
data, obtained through quantitative methods. This helps in the
interpretation of the research inquiry.
x. Use measuring devices :
To evaluate or collect quantitative data from the field, advanced digital or
electronic tools are used. When the tools are adjusted, they guaranteed the
complete and reliable data colle ction. Adjustment means that the
measurements of the researcher's tools match those of a reference
instrument that serves as a guideline.
6.4.2. Methods of Quantitative Research :
Quantitative methods are often more relevant for some research topics
since quantitative research offers more objective findings as they are based
on more reliable numeric data. Quantitative research can be carried out in
two ways. They are as follows:
A. Primary quantitative research methods
B. Secondary quantitative research methods
A. Primary quantitative research methods :
Primary research differs from secondary research. In primary research the
researcher collects data directly rather than relying on data from prior
studies. The primary quantitative research design can be categoris ed as
follows :
i. Survey Research:
The most basic tool for all quantitative research is survey research. Online
polls, online surveys, questionnaires, web -intercept surveys and other
types of surveys are used to collect data. This type of study can be
conducted with a specific targeted sample group with comparative study.
The sample of respondents must be randomly selected which is a
requirement for this research. Because a large variety of respondents will
be addressed using random selection a researcher can easily maintain the
accuracy of the conclusions.
ii. Correlational research:
Correlation research is used to identify a connectivity between two
variables, as well as how one influences the other and what changes are
observed as a result. This quantitati ve research method is used to assign
value to naturally occurring relationships and it requires the participation
of at least two different variables to be effective.
Researchers use this quantitative research design to correlate two or more
variables. Pa tterns, relationships and trends between variables are
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101 iii. Causal -comparative research:
This research technique is basically based on the comparison criterion.
This quantitative research method also known as quasi -experimental
research is used by researchers to determine the cause -effect relation
between two or more variables in which one variable is dependent on the
other independent variable. The independent variable is set up but not
changed a nd the effect it has on the dependent variable is measured. These
variables must be formed in the same way that they occur in reality.
Causal -comparative research is not limited to statistical analysis of two
variables, but also includes examining how vari ous variables or
phenomena interact to each other.
iv. Experimental research :
True experimentation also identified as experimental research is a research
method that is based on a hypothesis. Experimental research is usually
based on one or more theories. An analysis is carried out in experimental
research to prove or disprove the statement. In natural sciences, this
research method is used. In experimental research, there can be multiple
theories. A statement that can be verified or disproved is referred to as a
theory.
B. Secondary quantitative research methods :
Secondary quantitative research is a type of research that relies on
secondary data. To improve the overall effectiveness of research, current
data is summarized and compiled. This method of research entails
collecting quantitative data from existing data sources such as the internet,
government resources, libraries, and research reports, among others.
Secondary quantitative research aids in validating data collected through
primary quantitative resear ch, as well as improving or dismissing collected
data.
The following are some of the most commonly used secondary
quantitative research techniques:
i. Internet -based information :
With the widespread use of the internet and mobile devices, conducting
quantit ative research on the internet has now become increasingly simple.
Most research topic information is available online, which helps to
validate primary quantitative data and establish the relevance of collected
data.
ii. Government and non -government sources:
Government and non -government sources that engage with research
reports can also be used to undertake secondary quantitative research. This
data is extremely trustworthy and comprehensive, so it can be used to
improve the authenticity of quantitative rese arch designs.
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102 iii. Public libraries:
Although they are now a rarely used method of conducting quantitative
research, they are still a credible source of data. Public libraries have
copies of important studies conducted in the past. They are a source of
import ant data and documents from which data can be obtained.
iv. Educational institutions:
Educational institutions undertake in -depth research on a variety of
subjects and the findings that they publicly release a valuable source of
quantitative research ver ification.
v. Commercial information sources :
Local newspapers, journals, magazines, radio stations and television
stations are excellent sources of data for secondary quantitative research.
These commercial information sources really provide first -hand
infor mation on economic trends, political interests, market analysis,
demographic segmentation and other topics.
6.4.3. Data collection methodologies in quantitative research :
Collection of data is the most important part of conducting primary
research method . Sampling methods and data collection through surveys
and polls are two types of data collection methods.
Data collection methodologies : Sampling methods .
For quantitative research, there are two main sampling methods:
a. probability sampling and
b. non-probability sampling.
Probability sampling :
In probability sampling a theory of probability is used to search
individuals from a population and create samples. Random selection
methods are used to select participants from a sample. Every member of
the targe t population has an equal chance of being chosen for the sample.
It's mostly used in quantitative studies. Probability sampling techniques
are the best option for producing results that are representative of the
entire population.
Sample vs. population :
We must understand the difference between a population and a sample, as
well as identify research's target population.
Population : The population refers to the entire group about which
researcher wish to draw conclusions. Geographic location, age,
income and a variety of other characteristics can all be used to define the
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103 Sample : The sample is the group of people from whom
researcher will collect information.
It's absolutely essential to carefully define target population in view of
researche r’s research objectives and practical aspects.
It may be difficult to obtain a representative sample if the population is
very large, demographically diverse and widely scattered.
There are four main types of probability sampling :
i. Simple random sampling :
When the sample population is significantly larger, this sampling
technique is used.
Example : Researcher want to choose a simple random sample of 100
from Company X employees. Researcher assign a number from 1 to 1000
to each employee in the company d atabase and choose 100 numbers using
a random number generator.
ii. Stratified random sampling :
In this method, a large population is divided into groups i.e., strata and
units of a sample are selected at random from the strata.
Example : There are 800 femal e employees and 200 male employees at the
company. Researcher categorise the population into two strata based on
gender to ensure that the sample needs to reflect the company's gender
balance. Then researcher select 80 women and 20 men at random from
each group, giving a representative sample of 100 people.
iii. Cluster sampling :
Cluster sampling is a probability sampling method in which the main
segment into clusters, typically based on geographic and demographic
categorization criteria. Example:The firm has o ffices in ten different cities
across the country (all with roughly the same number of employees in
similar roles). Researcher don't have the resources to visit every office to
collect data, therefore researcher will use random sampling to select three
offices as clusters (groups) .
iv. Systematic sampling :
Systematic sampling is a technique in which the sample's starting point is
chosen at random and all other elements are chosen at a
predeterminedinterval.
Example: All of the company's employees are lis ted alphabetically.
Researcher choose a starting point at random from the first ten numbers:
i.e.,number 6. Every tenth person on the list is chosen from number 6
onwards (6, 16, 26, 36, and so on), resulting in a sample of 100 people.
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104 Non-probability sam pling :
Researchers used this sampling method for knowledge and experience.
Because of the researcher's intervention not every member of a target
population has the same chance of being chosen to be a part of a sample.
This sample is less expensive and ea sier to obtain, but it has a higher risk
of sampling bias. As a result, the researcher's ability to make population
inferences is limited compared to probability samples and conclusions
may be limited. A non -probability sample should still be made as
repre sentative of the population as possible. Non -probability sampling
techniques are frequently used in exploratory and qualitative research.
Rather than testing a hypothesis about a large population, the goal of this
type of research is to develop an initial understanding of a small or under -
researched population.
There are five different types of non -probability sampling models.
i. Convenience sampling :
In convenience sampling, sample are selected purely on the basis of
proximity to the researcher. Because thi s sampling is quick and simple to
incorporate. This is a quick and low -cost way to collect preliminary data,
but there's no way to know if the sample is representative of the
population, so the results aren't generally applicable.
Example : If a researche r is conducting research into student support
services at the university where he or she is pursuing a degree, the
researcher asks classmates to fill out a survey on the topic after each class.
Although this is a convenient method of gathering data, the sa mple does
not represent all students at the researchers' university. Because the
researcher only surveyed students who were in the same classes and at the
same stage as the researcher.
ii. Voluntary response sampling :
A voluntary response sample, like a conve nience sample, is primarily
based on accessibility. People volunteer themselves rather than the
researcher selecting and directly contacting them . due to some people are
inherently more likely to volunteer than others, voluntary response
samples are alway s skewed.
Example : Researcher distribute the survey to all students at its university,
and many of them choose to participate. Although this can provide some
insight into the topic, the people who responded are more likely to be
those who have strong opin ions about student support services, so
researcher can't be certain that their views are representative of all
students.
iii. Consecutive sampling :
Consecutive sampling is similar to convenience sampling, except that
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105 research on them for a long time and also repeat the process with different
samples.
iv. Quota sampling :
Quota sampling allows researchers to develop strata by selecting
samples based on their knowledge of target attributes. Acco rding to the
researcher's perception, members of various strata can then be chosen to
be a part of the sample.
v. Snowball sampling :
Snowball sampling is used to reach out to difficult -to-reach target
population and obtain information. Snowball sampling can be used to
recruit participants via other participants if the population is difficult to
reach. It's common in conditions where assembling a research target
audience is difficult.
Example : If a researcher searching into homelessness in the city. Because
there is no list of all homeless people in the city, probability sampling is
impossible. After meeting one person who agrees to participate in the
study, the researcher is introduced to other homeless people in the area.
vi. Judgmental sampling :
Judgmental sa mpling is a non -probability sampling method in which
samples are formed purely on the basis of the researcher's knowledge and
expertise. This type of sampling, also known as purposive sampling,
requires the researcher using their knowledge to choose a sam ple that is
most useful to the research's objectives.
It's frequently used in qualitative research, especially when the researcher
wants to learn more about a specific phenomenon rather than making
statistical inferences, or when the population is small an d specific. A good
purposive sample should have clear inclusion criteria and rationale.
Example:
If research is about disabled students' perspectives and experiences at
researchers university, so researcher purposefully select a group of
students with va rying support needs in order to collect a diverse set of data
on their interactions with student services.
6.5. QUALITATIVE RESEARCH V/S QUANTITATIVE
RESEARCH
Quantitative methods do not reveal the motivation behind participants'
responses, rarely reach minoritized populations and collect data over long
periods of time. Hence, it is best to combine quantitative methods with
qualitative methods. The distinctions between qualitative and quantitative
research can be drawn on the basis of the following facto rs:
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106 QualitativeResearch Quantitative Research
1. Qualitative research aims to
discover how people think and feel
in the human and social sciences 1. Whereas quantitative research
is a scientific and empirical
research method that employs
statistical, lo gical and
mathematical techniques to
produce numerical data.
2. Qualitative research is more
comprehensive. 2. Quantitative researchis more
specific or scientific.
3.Qualitative research takes a
subjective approach because the
researcher is involved di rectly. 3. Quantitative research takes an
objective approach because the
researcher is indifferent and tries
to identify the observations and
evaluation on the topic to address
questions.
4. Qualitative research is a type of
experimental studies. 4. Quan titative research is
conclusive.
5.The reasoning used to summarise
data in qualitative
researchconceptual. 5. Reasoning in quantitative
research the is scientifically
rigorous.
6. Purposive sampling is used in
qualitative research to select a small
sample size in order to gain a
thorough understanding of a
particular theory. 6.Quantitative research is based on
random sampling in which a large
sample is selected in order to
interpret the findings to the entire
population.
7. In qualitative research,
interpersonal data is collected. 7. Quantitative research collects
quantifiable data.
8. Words, pictures and objects are
used in qualitative research analysis. 8. Numerical data is used in
quantitative research analysis.
9. The goal of qualitative researc h is
to explore and discover ideas that are
used in existing practices. 9. In quantitative research, the goal
is to investigate the cause -and-
effect relationship between the
variables.
10. Qualitative research employs in -
depth interviews, focus groups and
other techniques. 10. Structured interviews and
observations are used in
quantitative research.
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107 6.6. INTEGRATING TECHNOLOGY IN DATA
COLLECTION
Data integration is the process of combining data from multiple
applications to create a unified conclus ion about of data. Data integration
is very critical process since data comes from multiple sources. Data
integration would be useful to consolidate data from various databases
and for reporting and analysis.
A - Methods of Data Integration:
When data come s in the form of a variety of internal and external sources
then data integration initiatives become necessary. Depending on the
discrepancies, ambiguity and number of data sources involved, following
are the different types of data integration techniques.
B - Surveys &Polls:
Once the sample size has been decided, surveys or polls can be used to
collect data for quantitative research. Among the most significant
methods for conducting quantitative outcome research is survey
because of the ease with which it can reach a large number of
respondents depending on the research time and objective.
“A survey is a research method for gathering data from a pre -determined
sample of respondents in order to obtain data.”
There are several methods for surveys. The followi ng are some of the
most commonly used methods :
i. Email :
The most widely used and most effective method of survey is sending a
survey via email. This method has a high response rate since respondent is
used to this method. Researcher can send and collect su rvey responses
using the emails.
ii. Incorporate a survey on a website :
Incorporating a survey on a website increases response rates because the
respondent can have access to survey anytime and from anywhere.
iii. Social distribution :
Distributing the survey v ia social media increases the number of responses
from people who are familiar with it.
iv. QR code :
The URL for the survey is stored in QR codes. This code can be printed or
published in magazines, on signs or on almost any other object or medium.
v. SMS surv ey :
An SMS survey is a quick and time -effective way to conduct a survey and
collect a large number of responses.
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108 C - Hand held devices for data collection:
In the social sciences, researchers have generally collected data using
paper -based devices, which have significant drawbacks and challenges.
Between the field and at the office data is at risk. Along with this such
data must be coded and analysed and need to be cross checked for
accuracy, which is expensive. Handheld devices are being used in research
to resolve such problems.
Handheld devices are any portable devices that can be carried and held in
one's palm. A handheld computer or electronic device is one that can be
held in one or both hands and operated. Although a handheld may include
cellular co mmunication, this category can also include other computing
devices. A handheld device is primarily intended to provide a set of
computing, communication, and informational tools in a device. Small
computing devices with a display screen and or a miniatur e keyboard are
known as handheld device technologies. These devices are usually
extremely lightweight and can be kept in a pocket and used while still in
your hand.
Following are some handled devices used in data collection.
Cell phone
iPad
iPod
Blackber ry
PDA
Handheld Computers
The handheld devices mentioned above are data collection devices and data
can be digitally recorded on the devices at the point of data collection. It
minimizes the need for entry of data after the data has been collected. Data
collection with handheld devices is more productive and makes sure
quality of the data. Furthermore, data validation and a reduction in manual
input help to reduce errors and save time.
Because the data collected by handheld devices is automatically synced
between device and user, researchers can upgrade and make modifications
at any time and from anywhere. The ability to evaluate collected data in
real time and monitor projects is assisted by handled device data collection.
D - Limitations of handheld device s in collecting data :
i. Problems with connectivity :
Some areas do not have internet access, while others have a weak signal
which results slow downloading.
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109 ii. Issues with data synchronization :
iii. Geographical and Climate Conditions like rain, mountains, rem ote
areas limit the data collection via handled devices.
iv. Incorrect Clicks :
v. Researchers click links and buttons on touch devices with their fingers,
which reduces click accuracy significantly. This is also known as the
"fat finger problem."
vi. Less Context :
Handheld touch devices have smaller screens which results context may
be lost. This makes it more difficult for the researcher to get an
understanding of the page, compare alternatives, and recall past
information.
E -Text messages:
Compared to tradit ional data collection methods, researchers use text
messages to collect data because it collects data in real time. Small,
simple, prompts answer options should be included in text messages. If
respondents do not answer back, researchers should decide whet her and
when to send notifications, as well as when and how often to communicate
directly them for incomplete data. Messages are sent, received and stored
by data collection portals. They have the ability to validate responses and
send out error messages. To improve consistency in data handling,
researchers should establish a procedure for adding new and correcting
data. Researchers can ensure that participants can receive and reply to
messages at the time of enrolment. Issues about secrecy must be addresse d
by researchers.
F - Importance of Text messages in data collection :
i. Increase the response rate
ii. Enables a wider demographic to be reached
iii. Simplify the screening process and sample group management.
iv. Make research more cost -effective.
vii. Easil y follow up with participants
G- Social Networking in data collection :
Any information collected from social media platforms give insights into
the actions of users on the platform. Any type of data that can be collected
though the social media is referre d to as social media data. Data collected
from information people post publicly on social media is also referred to
as social media data. Social networking tools can be used to collect this
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110 Every social media platform relies on user's input to provide the best
possible outcome. Metrics such as the number of likes, increase in
followers, number of shares, engagement duration and more are included
in the social networking data. Social networking data is a type of big data
obtained from a respondent’s profile on social media platforms such as
YouTube, Snapchat, LinkedIn, Instagram, Facebook and Twitter.
H. Importance of social media in data collection :
i. Customising social media strategy :
Collecting data via social media can assist researchers in customising
social media strategies for each social network. Even more precisely
researchers can customise their approach based on their location or
demographics.
ii. Collection of data in real -time :
The ability to gather data in real -time i s one of social media's biggest
benefit. Within a few hours, social media data can help researchers
to assess the outcome.
iii. Important information about respondents :
Social media data provides important information about respondents.
Researchers can lear n what types of message respondents prefer, when
they want to see it and where they spend their online time etc.
iv. Understanding of respondents :
By using tools and data extraction techniques of social media researcher
understand how respondents are relate to subjects. Researchers can now
accumulate data from social media, the web, forums, news and blogs
relating to specific events, topics or within a specific audience group.
v. Understanding of communication and behaviour trends :
Social media has evolve d at a fast rate and it's essential to analyse and
comprehend how humans use it to communicate. It helps in understanding
communication and behaviour trends in general. Academic research is
beginning to address and utilize social media but this is still a developing
field.
vi. Availability of large respondents :
Social media provides a large respondent for research. Respondents and
researchers can connect on social media. Social media may be
researcher first and last chance of data collection.
vii. Access to pe rsonal information of respondents :
Social media sites give researchers access to personal information of
respondents. Because social media pages are written in the first person
and it's relatively simple to create own online persona. For many
researchers these personas in their research field helps in gaining
credibility .
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111 viii. The technology solutions and methods used to monitor social media,
including social conversations and emerging trends, which is known as
social intelligence and Social Media Listening. By using this these
platforms, the collected data can be analysed and used to create valuable
content and make research conclusions.
I. Different sources for collecting social media data :
i. Twitter :
Twitter Analytics is excellent for analysing because it lets researcher
to see the best and worst posts from any month and can download data on
likes, replies, retweets and other metrics among other things. To get a
sense of how respondents think and feel about a topic, researchers can
search for keywords on T witter at a more detailed level over specific time
periods and in specific locations also.
ii. Facebook :
Facebook analytics tab also includes detailed downloadable statistics.
Researchers can see demographic characteristics of the respondents who
like Faceb ook Pages, as well as the number of views on posts and videos.
iii. Instagram :
Instagram tools currently connects to some Facebook -provided Instagram
analytic tools directly. The analytics provide a lot of information on both
Instagram timeline and Instagram Stories posts, from viewership,
connect and engagement to days of the week and a breakdown of locations
by city and age groups. Although it is possible to look into hashtag
usage which can be useful. But it is difficult and complex to get more
detailed inf ormation on the images themselves without using a specialist
tool like Pulsar which provides vertical AI image analysis.
iv. YouTube :
In YouTube's analytics section, researchers can look at a variety of
metrics, such as video watch times, traffic sources to see where viewers
are coming from, and demographic characteristic reports. Other options
for social media research on YouTube include looking at the YouTube
Trending page and studying the view counts and comments on videos, but
these are difficult to aggre gate without a specialist tool. YouTube Creators
Academy is an excellent resource for learning about YouTube analytics.
v. Forums :
Trying to figure out what forum participants are saying about social trends
is a great way to learn about them. Respondents w ill either elaborate on a
topic or seek advice, so if a researcher can decode publicly posted forum
topics, they can gain insight into the various topics and themes, which
could be useful for social media research.
vi. News and blogs :
It's also important to keep track of what's being discussed in the news and
on blogs, as this can influence social media research – for example, a
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112 conversation. The researcher typically conducts this research , but tools
such as Google News and Pulsar can be used to search for news and blogs.
vii. Trends on Google :
Researchers can search volumes for various trends dating back to 2002
and compare multiple trends in a volume over time graph using Google's
free tren ds service. The researcher can also see the most popular topics of
the day and find related search queries that are commonly used in relation
to the researcher's topic. This is especially useful when comparing trend in
research from search and social media .
6.7. SUMMERY
We discussed quantitative, qualitative, primary, and secondary data, as
well as the benefits and drawbacks of each. We also looked at the
advantages and disadvantages of various data collection methods. After
reading this topic, you should be able to choose the most suitable data
collection method for your research question. The evidence you use to
solve your research problem is called data. You get the right data to solve
your research problem when you use the proper data collection method . A
perfect study is one that incorporates both data collection methods.
Although some areas only require one type of research data. The
information required by the researcher is the most important factor.
Qualitative research is more abstract than quantit ative research.
6.8. EXERCISE
Q. 1. Fill in the blanks :
i. ……………….research is a type of research that focuses on gathering
information through open -ended and conversational discussion.
(Qualitative, Quantitative, Numerical, Quantifiable)
ii. …………… research i s a systematic analysis of research problems
through the collection of measurable data and the application of
statistical, mathematical or technological methods.
(Qualitative , Quantitative , Ethnographic, all the above )
iii. The purpose of ………………research is to learn about different
cultures, challenges, motivations and contexts.
(Ethnographic, Case study, Record keeping, none of the above)
iv. ……….t echnique is also known as "Empirical Research" since the
outcomes are accurately and precisely measured.
(Qualit ative , Quantitative , Ethnographic, all the above )
v. …………questions are those that require respondents to select from a
limited set of pre -defined responses.
( Open ended, closed ended, both the above,none of the above)
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113 vi. ……………… research is used to identify a connectivity between two
variables.
( Causal -comparative, Experimental, Survey, Correlation )
vii. In ………….sampling a theory of probability is used to search
individuals from a population and create samples.
(Convenience, Voluntary response, non - probabil ity ,probability )
viii. The ………….is the group of people from whom researcher will
collect information.
(Sample, survey , population, mean)
ix. ………….sampling is used to reach out to difficult -to-reach target
population and obtain information.
(Snowball, Quota, Judgmental, Consecutive)
x. In …………. sampling method samples are formed purely on the basis
of the researcher's knowledge and expertise.
(Snowball, Quota, Judgmental, Consecutive)
Q.2.Match the Column :
A B
i Closed ended questions Quasi -experimental research
ii Causal -comparative
research Secondary quantitative research
iii Internet -based information large population is divided into
groups
iv Stratified random sampling People volunteer themselves
v Voluntary response
sampling Yes/NO
vi Judgmenta l sampling purposive sampling
( Answers : i. Yes/No, ii. quasi -experimental research, iii. Secondary
quantitative research, iv. large population is divided into groups, v.
People volunteer themselves, vi. purposive sampling)
Q3. True or False :
i. One-on-one interview method is also known as unstructured
interviewing method.
ii. A case study investigates a real -time phenomenon in its natural
setting with the understanding that context matters.
iii. Quantitative data is collected using structured techniques such a s
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114 iv. In secondary research the researcher collects data directly rather than
relying on data from prior studies.
v. Secondary quantitative research aids in validating data collected
through primary quantita tive research.
vi. The sample refers to the entire group about which researcher wish to
draw conclusions.
vii. In convenience sampling, sample are selected purely on the basis of
proximity to the researcher.
(Answers : i. True, ii. Ture, iii. True, iv. False, v . Ture vi. False, vii.
True,
Q.4. Short Notes :
i. Explain the concept of qualitative data.
ii. Define and explain the concept of quantitative data.
iii. Types of Probability sampling
iv. Survey and poll
v. Hand held devices for data collection
vi. Write note on text m essages as a data collection tool.
Q.5. Answer in Brief :
i. Explain the features of qualitative data.
ii. Explain the types of qualitative data.
iii. Explain the features of quantitative research.
iv. Explain the primary method of quantitative research.
v. Explain the secondary method of quantitative research.
vi. Elaborate types of non -probability sampling method.
vii. What are the glaring differences between qualitative and quantitative
research ?
viii. Explain the importance of social media in data collection.
ix. Explain the source s of social media in data collection.
6.9. REFERENCES
i. Baxter, P., Jack, S. (2008). Qualitative case study methodology: Study
design and implementation for novice researchers. The Qualitative
Report, 13, 544–559.
ii. Kaarbo, J., Beasley, R. K. (1999). A pra ctical guide to the comparative
case study method in political psychology. Political Psychology,
20, 369–391.
iii. Sachdeva J.K.(2011). Business Research Methodology. New Delhi:
Himalaya Publishing House.
iv. Michael V.P.(1997). Research Methodology in Management . Delhi:
Himalaya Publishing House
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115 v. Ranjit Kumar (2014), Research Methodology : A step by step guide
for beginners, SAGE publication, ISBN :978 -93-515-0133 -6(PB)
vi. https://www.astera .com/type/blog/data -integration -techniques/
vii. https://www.researchgate.net/publication/12437403_Data_Collection_
Using_Handheld_Computers
viii. https://towardsdatascience.com/mobile -data-collection -what -it-is-
and-what -it-can-do-714dae3e0a18
ix. https://bmcmedresmethodol.biomedcentral.com/articles/10.1186/s1287
4-019-0891 -9
x. Regoniel, Patrick (January 3, 2015). Quantitative Research Methods:
Meaning and Characteristics [Blog Post].
Retrievedfrom https://simplyeducate.me/2015/01/03/quantitative -
methods -meaning -and-characteristics/
xi. https://www.ques tionpro.com/blog/quantitative -research/
xii. https://www.scribbr.com/methodology/sampling -methods/
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116 7
DATA PROCESSING, ANALYSIS,
REPORT ING – I
Unit Structure
7.0 Objective
7.1 Introduction
7.2 Stages in Data Processing
7.3 Data Analysis
7.4 Summary
7.5 Exercise
7.0 OBJECTIVE
1. To understand the role of data processing in business research.
2. To acquire th e importance of data processing in business research.
3. To develop knowledge about various methods of data processing in
business research.
4. To understand concept of Data Analysis
5. To learn various data analysis tools used by researcher
7.1 INTRODUCTION
Resea rch in the social sciences is conducted by adopting a battery of
diverse methods. This is because the social sciences represent a wide
variety of disciplines, including (but not limited to) psychology, sociology,
political science, anthropology, communicat ion, education, management,
and economics. Further, within each discipline, researchers can use several
different methods to conduct research. These methods can include
unobtrusive observation, participant observation, case studies, interviews,
focus group s, surveys, ex post facto studies, laboratory experiments, and
field experiments.
Despite this diversity in methods used and topics investigated, most social
science research still shares several common characteristics. Regardless of
field, most research i nvolves an investigator gathering data and
performing analyses. Analysis of data requires data processing, it involves
different techniques such as editing, classification, coding and tabulation.
The purpose of this chapter is to explain some of the fundam ental concepts
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117 7.2 STAGES IN DATA PROCESSING
Application of data processing by use of various statistical techniques not
only improves the accuracy of the data but the inference for the purp ose of
managerial decisions is more perfect and precise. Processing of data
includes removing unwanted, incomplete and irrelevant data and retaining
useful, correct and reliable data.
There are many modern sources used for data collection and processing.
After the invention of the internet, pen and paper -based research is losing
its glamour and all the activities of data collection are mostly conducted
by using modern methods like google forms. The use of automation makes
the data collection process smooth and better, but it also loads a lot of
additional requirements for data processing.
There are two methods adopted for data processing when computerised -
enabled research is conducted, for data processing those are
1 Batch processing and
2 Real -time data processing.
Batch Processing: In batch processing the raw data is collected and
further processed in specific batches, it is used for large quantities of data
sources such as payroll systems.
Real Time Processing: Sometimes the required data is needed to be
captured during the processing like we need to capture the data when the
customer is using the ATM to understand the usage behaviour, such
transaction -based data needs to be captured within seconds as soon as the
process starts. A huge transactional data is essential for making the
analysis more applicable and meaningful, only real -time data processing is
suitable for such a method.
Data processing is supplemented by the following activities:
7.2.1 Editing
Usually, business research is conducted throu gh some type of survey.
Such data collected from the field activity should be processed and
systematically analyzed as pre -decided in the research plan. Editing is the
process of improving the quality of data. It is concerned with removing
unwanted and irr elevant data, rectifying errors and filling in missing data.
Definition:
According to Luck Wales and Taylor, “Editing is the process of
inspecting, correcting, and modifying the information submitted on each
questionnaire so that it is stated correctly, ad equately and on a basis
common to all similar categories of reply.
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118 7.2.2 Objectives of Editing
1. Accuracy of Data : The primary objective of editing is to ensure
accuracy of data collected to find out the answer to the research problem.
Editing removes irrel evant and extra data and retains accurate data which
is helpful in further processing. It also removes clerical or other errors
from the collected data.
2. Consistency: Editing ensures consistency of data. It is highly
important to have consistency in data fo r effective data analysis and
correct results. Editing involves checking of data to remove any
inconsistency, ambiguity and errors to ensure its consistency.
3. Complete: Editing includes evaluation of data for its completeness.
Editing requires filling of mi ssing data to make it complete. A complete
data is helpful in obtaining desired result from data analysis
4. Facilitates Coding: Once editing is done it is important to codify
data for further processing. Proper editing helps in easy and proper
codification o f data. Proper codification of data helps in further processing
of data.
5. Acceptable for tabulation: Tabulation is an important step in data
analysis. It is an important objective of editing that the data should be
acceptable for tabulation. A good editing ensures the same and avoids
rejection.
7.2.3 Types of Editing
Editing is an important part of data processing. If a researcher wishes to
have accurate results for his study, he needs to ensure accurate data is
processed. Editing plays an important role by taking care of accuracy of
data used for processing and interpretation. Editing can be done either at
the time of collecting data or after collection of data is over. Based on
when data is edited there are two types of editing, a) Field Editing and b)
Central Editing
A - Field Editing:
This type of data editing is conducted immediately after the respondent
returns the data collection tool as a continuous process of review by the
person who had administered the tool of data collection. It is immediately
conducted as soon as the data collection instrument has been returned by
the respondents. Filed data edition has the process of matching the
respondent’s intention to the actual responses given.
This form of editing eliminates the potential troubles arising due to
discrepancies arising in view of the writing of individuals, which vary
from person to person and are sometimes difficult for the tabulator to
understand. This sort of editing should be undertaken as soon as possible
and immediately after the inter view, as it may be possible sometimes to
recall the memory. While doing the field data editing, care must be taken
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119 omission, by simple guesswork and imaginary facts about estimat ion
about what would be the respondent had answered if the question had been
answered by the respondent.
B- Central Editing:
Central editing is also called office editing, it is carried out after the return
of all the data collection forms to the research office.
In a small field study, all the forms are thoroughly edited by a single
person (most suitably by the editor). And by a small group of persons in
case of a large -scale field study. The editor is expected to correct the
obvious errors, such as an en try in the wrong place, responses might be
recorded in slang terms where they should have been recorded in specific
units.
Sometimes, there can be some chances of responses may be inappropriate,
or some might be missing replies. The editor in such cases c an do the
necessary correction by critically reviewing the other information recorded
in the data form. If necessary, the respondent may be contacted for
clarification. All the incorrect replies, which are obvious, must be deleted
from the data form. The e ditor must be familiar with the instructions used
by the data collectors in the field at the time of data collection and the
codes used during the editing. Care should be taken when any new
(corrected) entry is made by the editor it should be in some disti nctive
form and should be unique, and it must be initiated by the editor. The
timeline i.e., the date of editing may also be recorded on the data form so
that it may be helpful in any future references.
7.2.4 Coding
Once data is edited the next step is co ding of data. It is essential for
analysis of data as it helps in managing the data. In the process of coding
some symbolic value either alphabetical or numerals or both were
assigned to the responses so that the responses can be mathematically
processed b y recording them into a suitable and meaningful number of
classes or categories. The researcher needs to ensure that the classes
justify the appropriateness to the research problem proposed to be studied.
These classes must be exhaustive and should be mutu ally exclusive so that
the responses can be placed in one and only one cell in each category,
without any ambiguity. Further, every class must be perfectly defined in
terms of only one concept. The perfect coding ensures the efficient
analysis of data.
7.2.5 Guidelines for Coding of Data:
1. Use of Symbols and Alphabets: It is necessary to use symbols and
alphabets in coding, so it helps in data processing.
2. Appointment of Experienced Person: It is necessary to appoint a
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120 data. This helps in development of codes to be assigned for collected data
as well as framing of questionnaires.
3. Use of Appropriate Questions in Questionnaires: It is easy to codify
closed ended questions but it is highly difficult to code open ended
questions. Care needs to be taken to avoid such questions, however if use
of open -ended questions is inevitable then proper care has to be taken
while coding responses of such questions.
4. Use of Precoding: The coding d ecisions should usually be taken at the
very early stage of research designing and need to be incorporated in the
questionnaire itself so that the likely responses to the questions can be
suitably pre -coded.
5. Use of Categories: Coding involves deciding the categories to be used.
Categories should be mutually exclusive but should include all variables.
This should support the computer tabulation of the data for further
analysis.
6. Identification of Respondents and Responses : It is necessary to
identify responses and respondents, for this a unique alphabet or number
could be assigned to the respondents or the key information asked in the
questionnaire as well as responses received for the questionnaire. This will
be helpful in further processing of data.
7. Periodical Review: It is necessary to conduct regular check on
application of coding to ensure consistency, uniformity of data which is
helpful in further processing.
7.2.6 Classification
Meaning : In most of the social and business research studies, v oluminous
raw data is collected through the field surveys. For any meaningful
analysis such data needs to be reduced into specific homogeneous groups.
This is conducted through a process called classification of data.
Definition: It is a process of group ing of data in the basis of certain
criterion such as age, sex, income etc.
In simple terms it is the process by which the data is arranged in -to groups
represented by classes based on some specific characteristics. The process
of classification leads for condensation of the data and facilitates
comparisons; it also helps to study the relationships and accommodates
various statistical treatments on the data. To ensure the meaningful
analysis of the data it is needed that the data classification should be
conducted in an unambiguous and mutually exclusive and collectively
exhaustive manner. Further, it should not only be flexible but also suitable
for the research purpose prescribed and it should address the purpose for
which it is sought.' The system of cla ssification can either be according to
the data attributes or by assigning the simple numerical characteristics to
the data.
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121 7.2.7 Methods of Data Classification:
Data can be classified on the basis of similarity of attributes of data.
Following are dif ferent methods of classification of data.
1. Geographical Classification: Under this method data can be
classified on the basis of area or geographical area. For economic data
such as Income Level, Sales, Expenditure can be classified on the basis of
city, st ate, country etc.
2. Periodic Classification: This method of data classification is
focused on period or time. Data can be classified on the basis of time for
eg. monthly sale, weekly sale, yearly profit etc.
3. Qualitative Classification: This method of classifi cation is based
on unique feature of data collected. For example data can be classified on
the basis of Sex, Age, Income etc.
4. Quantitative Classification: This type of classification is focused
on attributes of data which could be measured in numbers. Data can be
classified on the basis of height, weight, income, profit or loss etc.
Classification of data can be done alternatively as follows.
Classification by the data attributes:
In this classification the descriptive characteristics of data attributes we re
used such as gender, education, family size, residential location etc. These
descriptive characters are usually those which cannot be measured in
quantitative units. Hence, those characteristics can only be described to
show in terms of either its prese nce or absence in a data pointer. The
classification according to attributes may be conducted in two types.
i) Simple Classification: Under thesimple classification each class is
divided into two subclasses and only one attribute is studied e.g., the
characteristics such as married or unmarried, employed, or unemployed
etc.
ii) Manifold Classification: In the case of manifold classification more
than one attribute of the same respondent are captured for in -depth studies.
For example, the respondents in a survey may be classified according to
their residential location as rural and urban buyers of a particular brand of
product. Both rural and urban users were further classified under
categories as user and non -user; it can be further classified into male an d
female. Further it can classify male and female into two categories such as
below 20 years of age and 20 and above years of age. The same
respondent can further be classified as professionals and non -
professionals. This way the researcher can keep on add ing more attributes.
This is shown in Figure – 9.1 below. However, the addition of any
attribute (in the process of sub -classification) only depends upon the basic
research objective and purpose for which the classification is carried out.
The researcher m ust clearly spelt out the objectives of such manifold
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122 Figure – Manifold Classification
(Source: Primary Data)
Classification by the numerical characteristics:
The Classificationby the numerical characteristics is perfect to represent
the numerical data such as sales, profits, height, weight, income, marks.
Such data can be easily classified into the class intervals. For example, the
respondent whose monthly income is between Rs. 5,001 and Rs. 9,999
may be classified under one group, those whose income is within Rs.
10,000 and Rs. 10,999 may form another (next) group, and so on. In this
manner, the entire data can be divided into a specific number of ‘groins or
classes, which are usually called class -intervals.
The number of such items fol lowing in such classes is called the.
Frequency of the class. Every class has two boundaries also called the
limits such as an upper limit and a lower limit, which are known as class
limits. The numerical difference between these two limits is called the
magnitude of the class or the width of the class interval.
The class intervals may be designed by using inclusive and exclusive
methods . Suppose in class intervals with class limits such as 10 - 15, 16 -
21, 22 - 27 etc. the class interval is an example of inclusive method
because the data represented by both the lower and upper limit are
included in the specific class only. If a variable ‘X’ falls in the first -class
interval, it can take values like 10< X >/=15. But if the class intervals
were designed lik e 10 - 15, 15 - 20, 20 - 25 etc. it forms an example of
exclusive class interval, because in this method the lower limit is included
whereas the upper limit is excluded from the specific class interval, e.g.,
the variable ‘X’ if falling in the first -class interval, would take values as
10
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Data Processing, Analysis,
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123 intervals using inclusive and exclusive methods , the following example
may be self -explanatory.
7.2.8 Tabulation
Next step in data processing is Tabu lation of Data. The process of data
tabulation is carried out by a specialist person and the act of tabulation is
very important. The process of tabulation serves two purposes i.e., the
summarization and the condensation of data.
Data Tabulation aids in a nalysis of relationships in the two data
characteristics. Tabulation if conducted with respect to ‘time’ it may
provide trends and other formats of the summarization of the given data.
Definition: The Process of tabulation involves numerical processing of
classified data which summarises the data by counting or totalling the
responses within each category of data.
The tabulation can be simple or complex. Simple tabulation is conducted
by adoption of a one -way table; it can be used to answer those questions
related to only one characteristic of the data. The complex tabulation
usually needs to be used a two -way table, it gives information about two
characteristics of the data; by projecting the inter -relationships in the
defined data characteristics, a three -way table which can give information
about three interrelated characteristics of the data; and in this manner still
higher order tables may be formatted, which has a capacity to project
information about several interrelated and complex characteristics of data.
7.2.9 Methods of Tabulation:
There are two methods of tabulation 1) Hand or Manual Tabulation and 2)
Machine Tabulation
1. Hand / Manual Tabulation: It is a traditionalmethod of tabulation.
It is simple to follow and execute. It is suitable for small data. In this
method sorting, numbering and counting of questionnaire / responses is
done manually. Tally marks are used for counting of data which enable
speedy data processing.
2. Machine Tabulation: This is an advanced method of tabulation and
is quite use ful when a researcher is handling huge data. It includes use of
machines such as computers for sorting, counting of responses. This
method is a costly method of tabulation as it requires machines to be
purchased. However these machines do not help only in tabulation but
could be used in entire data processing operations.
7.3 DATA ANALYSIS
Data analysis is an attempt by the researcher to summarize the data
collected in a meaningful manner to support the research objective or
purpose. It is the presentation of the findings of the study. Depending on
the nature of the data the tools of interpretation are required. Data analysis
and interpretation are the critical stages in the research process that munotes.in
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124 requires the researcher to apply knowledge of the data and its meaning by
establishing the relationships between the dependent and the independent
variables.
Meaning: Data Analysis is the process of systematically describing and
illustrating the meaning possessed by the data, by applying relevant and
suitable statis tical and/or logical techniques.
Definition: Data analysis can be defined as the process of transforming
collected data into useful information helping in drawing conclusions and
assisting in decision making.
While data analysis in qualitative research ca n include statistical
procedures, many times analysis becomes an ongoing iterative process
where data is continuously collected and analyzed almost simultaneously.
Indeed, researchers generally analyze patterns in observations through the
entire data colle ction phase. The form of the analysis is determined by the
specific qualitative approach taken (field study, ethnography content
analysis, oral history, biography, unobtrusive research) and the form of the
data (field notes, documents, audiotape, videotape ). An essential
component of ensuring data integrity is the accurate and appropriate
analysis of research findings. Improper statistical analyses distort
scientific findings, mislead casual readers, and may negatively influence
the public perception of res earch. Integrity issues are just as relevant to
analysis of non -statistical data as well.
7.3.1 Steps in Data Analysis
Data Analysis is a systematic and scientific procedure to be followed by
researchers to obtain accurate results of his study. A researche r must
follow all steps of data analysis given below to obtain the proper result.
There following 5 Steps used in the Data Analysis
Step One:Asking the right questions: Accurate data is needed for data
analysis hence asking the right questions to the respo ndents is needed to
get a correct response. A good researcher should avoid asking leading,
misleading and double meaning questions to obtain a proper response
from respondents
Step Two:Relevant data collection: For proper data analysis data
collection shou ld be relevant and related to the research problem. A
researcher should not get fascinated by the irrelevant data as far as
possible one must stick to the scope of the research only.
Step Three:Data cleaning: Collected data needs to be cleaned for data
analysis. There may be unwanted elements in the form of outliers that are
extreme exceptions in the data. These types of elements create skew in the
data, hence should be avoided, or eliminated by a process called haircut.
Step Four:Analyzing the data: Once d ata is obtained, edited, coded,
classified and tabulated the researcher can go ahead with data analysis for munotes.in
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125 this he needs to use appropriate, logical and statistical tools so that
relations between different variables of data can be revealed.
Step Five:Int erpreting the results: Once data is analysed and results are
obtained it needs to be interpreted. The output of data analysis is in the
form of numbers and numbers can not talk about themselves. The role of a
researcher is to apply the logic and meaningful frame to reveal the
meaning.
7.3.2 Use of Statistical Tools in Data Analysis
A. SPSS:
It is one of the popular software used in branches of business and social
research. Its abbreviation SPSS stands for Statistical Package for the
Social Sciences. It’s mo st preferred software since it has a better user
interface and has a capacity to address all the data analysis related queries
that can be handled without knowledge of syntax writing skills. Basically,
it is user friendly and multiple data collected from t he respondents can be
entered in one raw and can be used selectively as per the situation of
demand. Graphical representation of data analysis results is possible in
this software. This program gives an extensive range of basic to most
advanced statistical functions such as, frequencies, cross -tabulation,
bivariate analysis etc.
Data files stored in other software formats like MINITAB, EXCEL, SAS,
R can be easily explored in -to SPSS without any chances of data loss is
the superior feature of this software. It is now a day more advanced with
added add -ons such as AMOS for structural Equation Modelling (SEM).
Features of SPSS :
1. In SPSS the data is stored in file extension “.sav” format. This makes
the process of manipulating, analyzing, and pulling data very si mple.
2. SPSS allows a user - defined set of variables in research models.
3. The tools of data management and data editing are very handy.
4. SPSS allows the researchers to design, plotting, reporting and
presenting in a very simple manner.
5. SPSS has a huge inventor y of a number of predictive models with ease
of operations.
B. SAS:
The full name of SAS is Statistical Analysis Systems. It’s a powerful
programming language. The components used for analysis are called
procedures. Each such procedure is designed to perf orm a unique activity
of data analysis such as data analysis, data management functions some
features are dedicated for different types of output either text based, or
graphical presentation of the data processed. It can access the data from
both the inter nal and the external database sources. It can manage and munotes.in
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126 retrieve the data from various sources. It can format and convert the data
in required formats easily. It uses tools like forecasting & modelling;
descriptive statistical analysis is possible where m ultiple variants are
operative in a model. It supports various computing environments.
Features of SAS:
1. Robust ability of data analysis it has a range of simple to advanced
analysis.
2. It has its own inbuilt libraries, supports analyzing and reporting the
data analysis
3. SAS syntax is easy to learn; the codes on which it operates are like
simple statements.
4. SAS has reduced the burden of coding for the common researchers.
5. SAS has an interactive log -window which keep the user instructing
about possible errors
6. SAS has a wide variety of studios which can be accessed from any
device connected with any browser.
C. MS -EXCEL:
Excel by Microsoft is a spreadsheet program used for recording and
analysing numerical data by applying various statistical tools. It is
component of Microsoft office suite. Excel was formerly code -named
Odyssey through development. It builds data in columns and rows. Every
spreadsheet of Excel is a collaboration of rows and columns that creates a
space called a cell. Each cell has a unique identifi cation assigned with
alphabetical letter and numerical value each such cell may contain a single
piece of data in any format such as text, value, or formula. Each cell
address comprises the column by alphabetical characteristics and number
symbolising the row. It fits with multiple operating Systems (OS) like
Windows, Mac -OS, Android and IOS.
Features of MS -Excel:
1. Excel has a simple but robust password protection that allows the user
to protect the data stored in the workbook.
2. Excel allows the user to condu ct the data filtering in the manner the
data manager expects.
3. There are two specific commands for data filtering, such as auto
filtering and advanced filtering for addressing the needs of simple
criteria and complex criteria.
4. Excel has an inbuilt feature o f data sorting by using some logical order
either in ascending or descending manner
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127 6. Excel has an additional data analysis tool called pivot table; it allows
you to get the data in any manner for the purpose of analysis.
D. MINITAB:
It is developed keeping in focus the specific need of the requirements of
data analysis of the SIX SIGMA professionals. The data input is
simplified so that it can be used for any type of statistical interpretation.
The managerial problems are provided solutions in an easy and faster
manner by the Minitab. It mainly helps in identifying the trends and data -
based patterns.
Features of Minitab:
1. Drawing the Pareto chart is very easily available in Minitab.
2. Each worksheet has a project manager feature which makes the data
user friendly.
3. Minitab opens with three windows such as A) session window, B)
Worksheet window and C) Graphics window simultaneously.
4. The graphical window opens when the graphics are asked to plot such
as Scatterplot , histograms etc.
5. It has MSA i.e., Measurement System Analysis it determines the
amount of variation mathematically.
6. It has a built -in ability to design research experimentations.
7. It covers support for three major data types such as numerical, text and
data and time.
7.4 SUMMARY
In the business research process, data analysis is very important and needs
to be conducted in a scientific manner. There are several steps designed
especially when the researcher is conducting quantitative research, since it
is full of numerical data. The researcher must understand the research area
and scope comprehensively and do the required processing, analysis and
finally interpretation with the help of various techniques and tools of
analysis depending upon the nature, scope and aims of the research being
conducted.
7.5 EXERCISE
Fill in the Blank
1. The main objective of ……… studies to acquire knowledge.
A. Exploratory B. Descriptive C. Diagnostic D. Descriptive
and Diagnostic
2. ……………… is concerned with discovering and testing cer tain
variables with respect to their association or disassociation
A. Exploratory B. Descriptive C. Diagnostic D. Descriptive and
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128
3. Tabulation can be done by ……
A. hand B. machineC. Hand and Machine both D. None of these
4. Editing done at t he back office is called: …………
A. Field Editing B. Central Editing C. Physical Editing
D. Back Editing
5. By coding the transformation of the raw data is converted
into……………….
A. Symbols B. Letters C. Signs D. All of these
6. The primary us e of a table is for ………….
A. Tabulating data B. Interpretation of data C.
Classification of data D. Coding of data
7. ……….. describes the table’s contents.
A. Title B. Body C. Stub D. Footnote
8. Summarization and condensation of data is served by………….
A. Tabulation B. Classification C. Coding D. Title to the data
9. ………….. classification is suitable for capturing multiple attributes
of the same respondent.
A. Multiple B. Simple C. Layered D. Composite
10. The …. decisions should usually be taken at the very early stage of
research designing.
A. Coding B. Classification C. Data Security D. Tabulation
Key:
Q. No. 1 2 3 4 5 6 7 8 9 10
Key A A C B D A B A A A
Match the Column
A-Group B-Group
1. A systematic arrangement of the
data a. Prior to C oding
2. Data may deceive the decision
maker if it has b. Data processing
3. Data Editing c. Subjective elements
4. One variable description d. Column of Table
5. Caption e. Simple Tabulation
(Key: 1 -b, 2-c, 3-a, 4-e, 5-d) munotes.in
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129 Short Notes
1. Types of Ta bulation of Data
2. Methods of Data Classification
3. Central Editing
4. Stages in Data Processing
5. SPSS
6. MINITAB
Review Questions
1) Describe the stage s involved in processing data
2) What is editing? Why is it undertaken?
3) Explain two major types of data editing generall y used in business
research.
4) What is Filed editing? How and when it is conducted?
5) What is Central editing? How and when it is conducted?
6) What do you mean by coding of data in research? Explain its
guidelines
7) What do you understand by classification of dat a?
8) Explain the commonly used data classification methods in business
research.
9) What is simple and manifold classification? In which specific type of
situations these methods are suitable?
10) Explain the important characteristics of a table.
11) What is data tabu lation?
12) What is simple and complex tabulation?
13) What is Data Analysis? Explain steps in data analysis
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130 8
DATA PROCESSING, ANALYSIS,
REPORTING - II
Unit Structure
8.0 Objectives
8.1 Introduction
8.2 Report Writing
8.3 Summary
8.4 Exercise
8.5 References
8.0 OBJECTIVE
1. To understand the role of data interpretation .
2. To understand the importance of data interpr etation .
3. To understand concept of report writing
4. To develop knowledge about different types and content of reports .
8.1 INTRODUCTION
Data interpretation is the next step after data analysis. Data analysis
includes application of statistical tools however r esults derived from
analysis provide us numbers. Researchers need to find meaning from these
numbers; it is done through data interpretation. It is a process of drawing
inferences from the processed data.
Meaning:
The numbers do not speak for themselves. Interpretation is a process by
which a meaning is attached to the data. Hence, interpretation needs to be
fair and needs to be done in a careful manner by applying judicious
judgement. The interpretation depends on the understanding of the
intellect and ex posure of the researcher. Hence, it is always better to
involve more than one interpreter.
The process of interpretation of data is a complex process and it involves
cognitive and technical skills. However, it is a human effort driven activity
and involv es contextual and affective aspects. This view is confirmed with
research on affectivity and cognition. While the affective aspects of
interpretation are recognized as important for the interpretation of data,
they were not sufficiently discussed in the li terature. Data interpretation is
the process of assigning meaning to the collected information, and it
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131 Interpretation of the data involves two parts:
1) presenting the result(s) of the analysis; and
2) providing additional information that will allow others to understand
the meaning of the results.
In other words, it means placing the results in a context of relevant
information. Obviously, the process of interpretation involves bo th
decisions making and the use of good judgments. The use of the term
results to refer to any information obtained from using analysis
procedures. In this way the term findings refer to the results which have
been agreed because of research objectives.
8.1.1 Importance of Data Interpretation
Data interpretation refers to the process of using diverse analytical
methods to review data and arrive at relevant conclusions. The
interpretation of data helps researchers to categories, manipulate, and
summaries the information to answer critical questions. Following are
some of the points which summarizes the importance of data
interpretation.
1. Creative Process: DataInterpretation is a creative process which
can be used to judge knowledge, experience and ability of t he researcher.
Different conclusions can be drawn by different researchers by
interpretation of the same data.
2. Connecting Link: Analysis of data itself does not provide any
logical answer to the problem. Data interpretation is the connecting link
between d ata analysis and report. Interpretation of analysed data helps to
draw conclusion which can be included in the report
3. Logical Reasoning: Interpretation of analysed data provides logical
reasoning and helps to arrive at definite conclusion and recommendatio ns
for the research
4. Provides Knowledge: Interpretation of data is helpful in providing
knowledge of the research subject, this is helpful in further research
studie s.
5. Makes findings more meaningful: Data interpretation helps
inmaking findings more meaningf ul and ready for implementation.
8.1.2 Steps of Data Interpretation:
Data Interpretation has four steps as follows:
1) Assemble the essential information,
The researcher must ensure that all the information that is relevant and
essential for data interpr etation, is available. Such important information
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132 A. À list of the dependent and independent variables under study.
B. classification of the sample in suitable segments.
C. The framework of sample used during the data collection
D. À researcher should ensure that a correct unit of measurement is
adopted in the data tables and graphs.
E. À general observations, such as habitat and weather information for
each sampling
F. date and site.
The researcher can select to put all the information in easy-to-read tables,
graphs, or maps to be available to the readers.
2) Develop findings:
Findings are observations about the data used in the research. Findings
should be in the form of the statements that summarise the important
points. Findings will hel p the researcher to reach conclusions, because
findings will help in forming a more thorough and accurate interpretation.
The researcher should look at the data and try to explain it only after
thoroughly observing and summarising the trends, patterns, or lack of
patterns.
Developing findings is a process in which the researcher is expected to
compare the actual and analysed results with the known standards
benchmarks or guidelines within the data set with the other data sets.
3) Develop conclusions:
Concl usions are researcher’s explanation about, why the data look a
specific way? The conclusions should relate back to the questions the
researcher had explored by asking in the beginning of the monitoring
program – those must be the same as the study question s.
4) Develop recommendations.
Recommendations are based on the research findings and conclusions.
They can take two forms: action that should be taken and further
information that should be gathered, to address the future requirement in
the research topic or area.
8.2 REPORT WRITING
Research report is a systematic document describing the research carried
out by elaborating about the procedure used and method adopted. It is
defined as, “It is the systematic presentation of the research objectives,
methods and procedure followed in the research work in a systematic and
universally acceptable written form”. In report researcher provides his
analysis, findings, interpretation, conclusion and recommendations for the
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133 For both the business and fo r the research firms it is essential to describe
the findings derived by the research work. A well -documented report
saves time, energy and addresses all resources such as money, and it
brings general acceptance about the problem statement.
8.2.1 Character istics / Essentials of a good report:
Every good report has certain characteristics some of the ideal report
possesses following features:
1. A good report should be made in proper format. It should be clear,
concise, accurate and well organised with appro priate sections
dedicated to each area.
2. Every new area should carry separate and precise headings.
3. A good report should be easy for the target audience for their
understanding.
4. The goodness of a report dependents on its quality of presentation, a s is
a key element of a successful report.
5. A good report must be designed with proper formatting, suitable
revising and accurate proofreading are some of the important process
stages to make a good report.
6. A good report should have an executive summa ry that presents all the
essential elements of the report from the introduction through to the
recommendations and outcomes.
7. A good report should be visually appealing and easy to read.
8. A good report must have proper and self -explanatory diagrams, fi gures,
charts, tables, and graphs which can add interest and grab the attention
of the readers to a report.
8.2.2 Types of Report
Almost all reports in business are derived according to specific situations
to help the decision making and explore the possib le outcomes in a
complex situation. There are different reports such as Sales Activity
Report, Personal Evaluation Report, Financial Report, Feasibility Report,
Progress Report, Credit Report. All these research reports are typically the
collection and pre sentation of the collected data to expedite the decision
making in a more scientific manner by providing the interpretation of data
by applying statistical tools. All these reports can be classified in -to three
groups:
1. Analytical Reports
2. Recommendat ion Reports
3. Informational Reports munotes.in
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134 Analytical Reports:
This type of reports is also called a “specialised report” and they are
prepared to address the quarries like why or how something happened and
then to explain what it means in the given context. An alytical reports
attempt to explain, what is the cause behind a problem, or a typical
situation faced by a business or an organisation. These reports are
generally conducted to find out the potential results if a particular course
of action is undertaken. They sometimes attempt to suggest which option,
action, or procedure is best. These reports attempt to describe the
analytical facts and reports with estimated results, and draw conclusions
based on those results.
Recommendation Reports:
These types of rep orts are prepared to advocate a specific course of action
to a company or an organisation or department of a company. This type of
reports is identical next to the analytical report. This usually presents the
best option based on the analytical report, con sidering the internal and
external business situation in which the organisation operates.
Organisations generally find it difficult why they should follow a certain
course of action or there might be many options hence, selection of the
most suitable optio n can be a biassed decision to avoid the
recommendation, report helps it to arrive at the proper course. Since these
reports are prepared at specific occasions they are also known as
“accidental reports.”
Information Reports:
Informational reporting is als o called “narrative report”, it is designed to
present a description of the situation so that the readers can understand a
particular problem or situation thoroughly. This type of reports is built by
collecting all the facts and relevant data, without deci ding the situation in -
to a typical type. Generally business managers who handle a wide and
variety of business operations for them the complexity of scope of
operation does not permit to be aware about all challenges faced by the
business hence for any sit uation which deviates beyond the bench marked
level an informational report is prepared. It presents an update of the
operation in a business division. Or it may explain how the organisation or
division does something. These are usually desk research and rarely they
are the results of a questionnaire or field research.
8.2.3 Contents of Report
1. Title page: It should include the title, the name of the preparator, and
the name of the authority to whom it is designed to be submitted. This
page also conta ins other details such as, the date of submission, the name
of the department, the logo of the organisation etc.
2. Acknowledgements: It is a list of individuals and certain people
belonging to organisations who have helped in the compilation of reports
and other related work. A reference is made to recognize the contributors. munotes.in
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135 3. Contents page: It is an index of all the sections and subsections
contained in the report. The index should be designed with page numbers,
and one should ensure that pagination be marked correctly. There can be a
separate index for figures and tables, depending on the volume of these
elements in the report.
4. Abstract: It is also called “executive summary”. It is a summary of
the major points, conclusions, and recommendations shoul d be written to
give a general overview of the report. Ideally it should not be too long.
5. Introduction: It is the first page of the report, which needs to have
an introduction of the topic. The researcher is expected to explain the
problem and show the reader clearly why the report is being made.
Specifically, the research objectives need to be mentioned at the very
beginning.
6. Body: This is the main section of the report. There needs to be
several sections, with each having a title and subtitle. Among the various
sections it may include Review of Literature, data sources and research
methods used and the results.
7. Methodology: This topic with the research method and research
framework and the sampling method adopted, more specifically it should
expla in the method used for data collection. And the time of data
collection from the field. Methodology should explain the sample
selection criterions also.
8. A discussion section: This section will summarise and explain at the
end of the body to go over by f indings and their significance.
9. Conclusion: A conclusion should draw out the implications of the
research findings. It may be based on the deductions based on the facts
described in the main body of the report. The significance and relevance
of the stud y is discussed in this section.
10. Appendix: Is a part which contains the additional details of the data,
maps of the sample collected site/ market location. It is basically a part
where all detailed supportive documents such as questionnaire, tables,
mathematical calculations are compiled and given a specific index
number, which inside the description is mentioned with a specific
reference no.
11. References: This is a list showing the full details of all the
information sources to which the researcher h as referred within the text.
8.2.4 Use of Audio -Visual Aids in Research Report
A picture speaks for a thousand words. This line itself elaborates the
importance of visuals. Inclusion of visual aids in the report increases
effectiveness of the report. A gra phical illustration helps the reader to
understand the point easily and effectively. munotes.in
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136 According to Ruben and Stewart (2006), AV (Visual Aids) function to add
interest to a presentation (in this case, a report) by giving the audience
(readers) something to j udge by allowing them to examine (easily). They
may also clarify what the sender is saying (writing) by providing a visual
illustration to the specific points described in the report.
There are four types of visual aid that help the readers to convey the
meaning to common and specific audiences:
1. The actual objective or rationale behind the discussion; the presenter
uses some suitable graphical object to make the understanding better.
2. The presenter may use a model so the model explains about the object
being discussed.
3. Meditation by suitable objects, such as pictures or illustrations.
4. Meditation by tools such as charts, graphs, and diagrams.
Advantages of Visual Aids:
Visual aids are the tools that help the presenters to clarify, establish, and
co-ordinate precise conceptions, understandings and appreciations and
support so as to make the understanding more real, active, motivating,
encouraging, significant and glowing.
1. Every individual has the tendency to forget. Proper use of visual aids
helps to retain more concepts permanently.
2. An individual can study well when the inspiration is properly provided
through different visual aids.
3. Visual aids grow the accurate image when the individual sees and
imagines it properly.
4. Visual aids provide complete examples for conceptual clarity as it
allows cognitive thinking.
5. Visual aids create the environment of interest for the stakeholders.
6. Visual aids help to increase the vocabulary and enriches the readers.
7. Visual aids help the readers to ge t the information by learning it
permanently.
8. Visual aids provide direct experience to the readers.
Graphic Formats
Many different graphic formats can be used to support the text’s main
ideas. However, the ideal graphic format depends on the type of dat a being
presented.
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137 1. Tables:
The table presents large amounts of data in a simple, brief, and clear linear
format. The same data in prose would be bulky, confusing, and
inaccessible. Tables allow the reader to grasp relationships that might be
invisible i n its prose format. Also, the tables allow the writer to focus
attention on specific pieces of data while retaining a clear presentation of
the whole idea to be described.
2. Graphs and Charts
Graphs are pictures that help the readers in understanding the data. There
are many kinds of graphs, each has a special purpose. Charts illustrate
generally for the comparison purpose, usually among several sets of
information. Many other sorts of chats are possible as described below:
1) Circle Graph: A circle graph is shaped like a circle. It is divided
into fractions that look like pieces of pie, so sometimes a circle graph is
called a pie graph. Many times, the fractional parts are different colours,
and a key explains the colours.
2) Bar Graph: A bar graph shows d ata in various types of bars/stacks.
The bars can be arranged vertically (up and down), or horizontally
(across).
3) Picture Graph: A picture graph uses suitable pictures or symbols
relevant to the characteristics of the data. One picture often stands for
more than one characteristic so the key in this type of graph is to
understand the symbols.
4) Histogram Graph: A histogram is a special kind of bar graph. This
is drawn to plot statistical measures graphically. Hence, the stacks are
connected to each othe r. The class intervals must be shown below,
sometimes less than or more than cumulative frequency is plotted as per
the purpose of analysis.
5) Line Graph: A line graph shows points plotted on a graph for a
specific scale of units. The points are then conn ected to form a line.
8.3 SUMMARY
Data Interpretation is the most important aspect of the research. It is the
process which is the basis for the research report. Interpretation helps the
researcher to draw inferences from the analysed data. Interpretation helps
to find out solutions to the research problem.
Report writing is the last stage in research. In this stage the researcher
provides his analysis, findings, interpretation, conclusion and
recommendations for the research problem. The report must be eas y to
understand and well drafted. Researchers can use visual aids such as
tables, graphs, diagrams, charts to increase effectiveness of the report.
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138 8.4 EXERCISE
Fill in the blanks
1. A good report contributes in….
A. saving time of the readers B. brings enjoyment to the readers
C. sav es money of the readers D. brings good teamwork
2. …. are those reports submitted to the senior executives?
A. Technical reports B. Popular reports
C. General reports D. Sample reports
3. ………….is also called a “narrative report”.
A. Informational reports B. Analytical Reports
C. Recommendation Reports D. Informative Reports
4. The findings derived from the research work are presented by ------
A. Report writing B. Diagrams C. Graphs D. Tables
5. ….. is also called “executive summary”
A. Abstract B. Title C. Tag D. Hasht ag
6. ….. is the main section of any report.
A. Body B. Introductio n C. Abstract D. Executive Summary
7. …. describes the research method and research framework and the
sampling method adopted in the research work.
A. Method ology B. Report writing C. Diagrams D. Graphs
8. … is a part which contains the additional details of the data, maps of
the sample collected site/ market location.
A. Appendix B. Reference C.Bibliography D. Index
9. …. is a list showing the full details of all the information sources to
which the researcher has referred.
A. Reference B. Append ix C.Bibliography D. Index
10. …………………function to add interest to a presen tation (a report)
by giving the audience (readers) something to judge by allowing them
to examine (easily).
A. Visual Aids B. Authors Photo
C. Symbol of the Organisation D. Foreign Language
11. A ……. graph is shaped is based on angular degrees like a circle
A. Pie chart B. Pictograph C. Bar Graph D. Histogram
Key:
Q. No. 1 2 3 4 5 6 7 8 9 10 11
Key A A A A A A A A A A A munotes.in
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139 Match the column
Column -A Colum n-B
1. Circular Graph a. Data - Stacks
2. Bar Graph b. 360 degree
3. Picture Graph c. Cumulative frequency
4. Histogram d. Point data
5. Line Graph e. Symbols
(Key: 1 -b, 2-a, 3-e, 4-c,5-d)
True or False
1. The commonly used rectangular diagrams belon g to the category of
the two -dimensional diagrams.
2. Proper use of visual aids helps to retain more concepts permanently.
3. A report should describe research objective of the study but not the
nature of the problem
4. Informational reports is also called “narrative report”,
5. A good report should not be visually appealing to read.
(Key: 1 -True, 2 -True, 3 -false, 4 -True, 5 -false)
Short Notes
Write short notes on:
a. Two dimensional diagrams
b. Pictograms
c. Pie Chart
d. Line or Arithmetic Chart
Answer in Brief
1. Why is report writing in business research an important aspect of
effective research?
2. Explain types of research reports.
3. Describe common contents of a business research report.
4. Explain major steps in writing a good research report.
5. Describe the Importance of report writing in business research.
6. What are the common types of reports suitable for business research? munotes.in
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140 7. Explain the role of Visual Aids (VA) in report writing.
8. Explain the advantages of Visual Aids (VA) in report writing .
9. Explain the various graphic formats used in report writing.
10. What is Data Interpretation? Explain its importance
8.5 REFERENCES
1) Adams, Mortrie R., “Annual Reports… Who reads them?”, 2012.
2) Pope, C., Ziebland, S., and Mays, N. (2000). ‘Analyzin g qualitative
data’. British Medical Journal, 320: pp. 114 –116
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