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1MODULE –I
INTRODUCTION TO RESEARCH
1
INTRODUCTION TO RESEARCH
Unit Structure
1.0 Objective
1.1 Introduction to Research
1.2. Types of Research
1.3. Summery
1.4. Questions
1.5. References
1.0OBJECTIVE
After studying this unit the student will be able to 
Understand the concept of Research
To understand the characteristics of Research
Know the Importance of Research in Business
Explain various Types of Research
1.1 INTRODUCTION
1.1.1 MEANING
The word ‘Research’ is derived from the Middle Fren ch word
‘recherche’ meaning ‘to go about seeking ’.Research is a careful and
detailed study into a specific problem, concern, or issue using the
scientific method. Also r esearch is a systematic investigation to search for
new facts in any branch of knowled ge. It helps to find solutions to certain
problems and arrive at new conclusions.
1.1.2 DEFINITION
According to The Organization for Economic Cooperation and
Development (OECD) ,"Any creative systematic activity undertaken in
order to increase the stock of knowledge, including knowledge of man,
culture and society, and the use of this knowledge to devise new
applications."
According to John W. Creswell , who states that "research is a
process of steps used to collect and analyze information to increase ourmunotes.in
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2understanding of a topic or issue". It consists of three steps: pose a
question, collect data to answer the question, and present an answer to the
question
William C. E mory defines “research is any organized inquiry
designed and carried out to provide information for solving a problem.”
Robert Ross defines “Research is essentially an investigation, a recording
and analysis of evidence for the purpose of gaining knowledge .”
1.1.3 FEATURES OF RESEARCH
1)Systematic Process: Research is a systematic process. No research
can be conducted haphazardly. Each step must follow other. There are
set of procedures that have been tested over a period of time and are
thus suitable to us e in research: The steps are as follows:
Formulating the research problem
Review of Literature
Define Research objectives
Preparing Research Design
Collection and analysis of data
Interpretation of data
Preparation of report
Follow up of report
2)Objective and Logical / Empirical: Researcher needs to make every
possible effort to avoid biasness in every stage of research process. In
order to make research objective and logical / empirical, there is a
need to collect relevant and accurate data to investigate into the
research problem. After collection of data, the researcher need to
undertake processing of data, analyse and interpret it and arrive at
logical conclusion. So the research has to be conducted following
rigorous scientific methods and procedures. E ach step in the research
has been tested for accuracy.
3)Development of Principles and Theories: A systematic research
helps to develop new principles and theories. Such principles and
theories can be useful to several organizations to manage and deal with
people and things in a better way. Eg. Prof. Alfred Marshall used the
inductive method of research in economics. On the basis of the market
analysis he framed ‘Lawof Demand’ .According to this law, there
exists a negative relationship between the price an d quantity
demanded. When price increases, demand falls and vice versa.
Another example could be, ‘14 Principles of Management by Henry
Fayol’. They are developed gradually with thorough research work.
Systematic observation and experiments are conducted i n various
organizations before developing them.
4)Multipurpose Activity: Research is multipurpose activity. It helps to
achieve multiple purposes such as:munotes.in
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3Discover new facts or verify old facts.
Predict future events and control such events
Establishes rela tionship between variables
Develop new scientific tools, concepts and theories
5)Basic and Applied Research: Basic or fundamental or pure
research is a research approach that is entirely theoretical and aimed
at improving or expanding the knowledge base of a particular field of
study. The main motivation in basic research is to expand man’s
knowledge, not to create or invent something. There is no obvious
commercial value to the discoveries that result from basic research. It
does not have direct commercial objective.
Applied research is designed to solve practical problems of the
modern world, rather than acquire knowledge for knowledge sake. In
other words, the purpose of applied research is to know more about a
certain real world problem and take steps to solve it. It has direct
commercial objective. Researchers in this field try to find immediate
solutions to existing problems facing a society or an industrial or
business organization.
6)Quantitative and Qualitative Research: Quantitative research
refers t o as a systematic investigation of phenomena by gathering
quantifiable data and performing statistical techniques. Eg. Research is
undertaken to find out the number of unemployed graduates. This type
of research is usually done by using surveys, experiment s, and so on.
Qualitative research is used to gain an understanding of human
behaviour, intentions, attitudes, experience, etc. It is based on the
observation and the interpretation of the people. Eg. Research is
undertaken to find out reasons as to why employees remain absent
from work.
7)Generalization: When the researcher conducts a research, he/she
selects target population and from this population, small sample is
selected for collecting data. So the sample selection must be done
systematically so tha t it represents the whole population or the
universe. The findings with this sample is generalized on entire
population/universe of research. Eg. A research is undertaken on
‘Consumer behavior towards electronic goods of Samsung Company
in Mumbai region’ a mong 500 sample size. The findings of these 500
samples may be generalized for people residing in entire Mumbai
region.
8)Reliability: It is a subjective term which can not be measured
precisely, but today there are instruments which can estimate the
reliab ility of any research. Reliability is the extent to which the
outcomes are consistent when then experiment is repeated more than
once. If research is undertaken with similar population and withmunotes.in
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4similar procedures, If it yields similar results each time it is called to
be a reliable research. . Eg. A research is conducted on ‘the effects of
single parenting on the class performance of the children’ and the
results conclude that single parenting causes low grades in class. These
results should have to be reli able for another sample taken from a
similar population. More the results are similar; more reliability is
present in the research.
9)Validity: Validity of the research instrument can be defined as the
suitability / accuracy of the research instrument to th e research
problem. Validity is the extent to which the instruments that are used
in the experiment measure exactly what you want them to measure.
Some researchers say that validity and reliability are co related, but the
validity is much more important t han reliability. Without validity,
research goes in the wrong direction.
1.1.4 IMPORTANCE OF RESEARCH IN BUSINESS
1)Helps to predict changes in business environment: The business
management is witnessing constant changes due to changes in external
busin ess environment such as:
Consumer preferences,
Competitor’s strategy,
Society expectations
Economic environment,
Technological environment,
Legal environment (macro factors) and so on.
This change in business environment can adversely affect a
busin ess organization. So the manager can timey predict such changes and
save business from heavy losses.
2)Launching new product: Business research helps in successful
launching of a new product in the market. This is because, a research
enables to know the lik es, dislikes, preferences and choices of their
consumers related to product. Accordingly a business firm can design
and launch new product. Such product has lower rejection rate and
higher acceptance from consumers. When customers are offered
product as pe r their preferences, it results into customer satisfaction.
3)Helps to design effective marketing strategy: Business research
helps to design effective marketing strategy. Research enables to a
business organization to:
Design quality product
Decide right price
Effective promotion
Proper distributionmunotes.in
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54)Achieve organizational goals: Systematic business research helps to
achieve organization goals such as:
Customer Satisfaction
Increase in sales and profits
Expansion of Business
Enhance Corporate image
Face co mpetition and so on.
5)Studying the competition: Companies often use business research to
study key competitors in their markets. The company may want to
know the percentage of customers in the market who purchase its
products versus competitor’s products. Also it enables to know the
marketing strategy of competitors. Accordingly a business firm can
design its own marketing strategy to survive and growth in the highly
competitive market.
6)Facilitates decision making: With the help of research data available ,
businessman can take right decision at right time. Research provides a
business with a chance to update itself the latest market trends. Such
knowledge will prove helpful in the formulating of useful tactics for
success in the market. It is through resea rch that a business is able to
make educated and informed decisions.
7)Helps to measure business progress: Business research enables to
gauge (measure) how well business is performing. Early research may
highlight problems in services and short falls in t he products. Regular
market research will show if improvements are being made and if
positive, will help to motivate a team.
8)Availability of competent manpower: Research also helps in the
recruitment and selection of competent manpower. Proper recruitmen t
and selection of employees with the right skills and attitudes help the
firm to increase its productivity levels. Further effective training and
compensation package can improve morale of employees and motivate
them to work with dedication and commitment .
9)Helps to get right suppliers: Research helps the firm to get a right
supplier who offers raw material at right price and right time. A proper
supplier selection enables the firm to get or acquire high quality raw
materials which result into production of high quality products that are
consumed by end users.
10)Improves productivity: Productivity refers to the ratio of output to
the input i.e. with one unit of input, how much output is produced.
Productivity can be increased with the help of:
Training to employees
Research and Development
Use of Modern Technologymunotes.in
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6Business research make realize to the business firm to undertake
these activities which result into improvement in productivity of
the business.
1.1.5 OBJECTIVES OF RESEARCH
1)To find out solution to problems: Research can be undertaken to find
solutions to solve a specific problem. Data is collected on the problem
faced by an organization. Such data is analysed and interpretation is
made to find out solution to solve the problem. Eg. An organizati on
may initiate research to find solution to problem of declining sales of
their product in the market. So the data is collected to find out reasons
for declining sales and analysis of such data may provide solution to
the problem.
2)To obtain Information: Research is undertaken to obtain information,
which may not be easily available. Variety of information can be
collected such as consumer preference, competitor’s strategy, demand,
economic conditions and so on. Such information is vital for a
marketer to take crucial marketing decisions.
3)To make future predictions: Research enables a businessman to
collect past and present data. Based on such data, the researcher can
make future predictions about business situation and business stand in
near future. Eg. A marketer wishes to launch a new product in the
market. With the help of research he can predict the future of that
product and then decide whether to come up with that product or not.
4)To develop new tools and concepts: Research helps to develop new
tools and concepts for better study of an unknown phenomenon. For
this purpose, exploratory research is undertaken to achieve new
insights into such phenomenon. Eg. Research enables a business firm
to know what factors affect consumer satisfaction in modern t imes.
Accordingly marketer can develop new tools and concepts to provide
maximum consumer satisfaction.
5)To verify and test existing laws or theories: Research may be
undertaken to verify and test existing laws or theories. Such
verification and testing o f existing laws and theories is required to
know the relevance of it in present time..
1.2 TYPES OF RESEARCH
1)Basic Research : Basic or fundamental or pure research is a research
approach that is entirely theoretical and aimed at improving or
expanding the knowledge base of a particular field of study. The main
motivation in basic research is to expand man’s knowledge, not to
create or invent something. There is no obvious commercial value to
the discoveries that result from basic research. It does not h ave directmunotes.in
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7commercial objective. Eg. “A study on socio economic status of
dwellers of Dharavi area, Mumbai” OR “A study on impact of mobile
phone on studies of secondary school children.”
2)Applied Research: Applied research is designed to solve practical
problems of the modern world, rather than acquire knowledge for
knowledge sake. In other words, the purpose of applied research is to
know more about a certain real world problem and take steps to solve
it. It has direct commercial objective. Researchers in this field try to
find immediate solutions to existing problems facing a society or an
industrial or business organization. Eg. “Investigating factors that
improve worker's productivity.” OR “A study on declining sales of
ABC soap.”
3)Descriptive Research: Descriptive research is a type of research that
provides an in depth description of the situation, phenomenon or
population under study. This research is also an appropriate option
when researcher does not have any information about the research
problem, and primary information gathering is required to establish a
hypothesis. The descriptive research provides the answer to the “what”
part of a research and does not answer the questions “why”.
Researcher has no control over the variables and researcher ha st o
report the actual conditions. For example, an apparel brand that wants
to understand the fashion purchasing trends among Mumbai buyers.
They will conduct a demographic survey of this region, gather
population data and then conduct descriptive research on this
demographic segment. The study will then uncover details on “what is
the purchasing pattern of Mumbai buyers,” but not cover any
investigative information about “why” the patterns exits. Because for
the apparel brand trying to break into this mark et, understanding the
nature of their market is the study’s objective.
4)Analytical Research: Analytical research is a critical evaluation based
on information that is available. The researcher makes use of facts or
information already available and analys e these to make a critical
evaluation of the material. It is primarily concerned with testing
hypothesis. It specifies and interprets relationships by analyze the facts
or existing information. The analytical research provides the answer to
the “why” part of a research. It is usually concerns itself with cause 
effect relationships. Eg. Explaining why and how US trade balance
move in a particular way over time.
5)Conceptual Research: This research is a type of research that is
generally related to abstract i dea (existing in thought or as an idea but
not having a physical or concrete existence) or concept. It does not
involve any practical experiment. This research is generally used by
philosophers and thinkers to develop new concepts or reinterpret
existing ones.munotes.in
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86)Empirical Research: Empirical research relies on the observation and
experience with hardly any regard for theory and system. Such
research is data based, which often comes up with conclusions that can
be verified through experiments or observation. For example: A
research is being conducted to find out if listening to happy music
while working may promote creativity? An experiment is conducted
by using a music website survey on a set of audience who are exposed
to happy music and another set who are not listening to music at all,
and the subjects are then observed. The results derived from such a
research will give empirical evidence if it does promote creativity or
not.
1.3 SUMMARY
This unit is about features of research and how research holds
significance in business. It also comprises objectives of undertaking
research and different types of research. So this unit gives basic ideas
about research which helps to plan the research activity and achieve
its objectives. So every researcher must know the features of research,
its importance and objectives as well as different types of research
before he/she actually starts with a research activity.
1.4 EXERCISE
FILL IN THE BLANKS
1)___________ is any organized inquiry designed and carried out to
provid e information for solving a problem
A)Sampling B) Research C) Hypothesis D) Research Design
2)The research should be ___________
A)Empirical B) Biased C) Subjective D) Inaccurate
3)____________ research refers to as a systematic investigation of
phenomena by gathering quantifiable data and performing statistical
techniques
A)Qualitative B) Census C) Quantitative D) Historical
4)___________ research is an appropriate option when researcher does
not have any information about the research problem
A)Analyti cal B) Descriptive C) Conceptual D) Basic
5)Research in business facilitates ____________
A)Design ineffective marketing strategy
B) Design various schemes for upliftment of backward regions
C) Availability of incompetent manpower
D) Forecast chan ges in business environmentmunotes.in
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9TRUE OR FALSE
1.Research can be conducted haphazardly. FALSE
2.Research helps to measure business progress. TRUE
3.Applied research has direct commercial objective. FALSE
4.Analytical research is a critical evaluation based on inform ation that is
available. TRUE
5.In research, reliability is the extent to which the outcomes are
consistent when then experiment is repeated more than once. TRUE
MATCH THE PAIRS
Group A Group B
1)Basic Research a)Achieve organizational goals
2)Empirical Resear ch b)Gathering quantifiable data
3)Quantitative Research c)Risarch
4)Objective of Research in
Businessd)Recherche
5)The word ‘Research’ is
derived from French worde)Relies on the observation and
experience
f)Also known as pure or
fundamental research
(1–f, 2–e, 3–b, 4 –a, 5–d)
ANSWER IN BRIEF
1)Define Research. Explain its features
2)“Research is important in Business.” Explain.
3)Discuss the objectives of research.
4)Write a note on:
Basic Research
Applied Research
Descriptive Research
Analytical Research
Empirical Research
1.5 REFERENCES
https://en.wikipedia.org/wiki/Research#:~:text=The%20word%20resea
rch%20is%20derived,th e%20term%20was%20in%201577.
https://readingcraze.com/index.php/characteristics research 2/
https://www.slideshare.net/darious91/importances ofresearch in
business
https://research methodology.net/descriptive research/
https://www.marketing91.com/descriptive research/
https://www.ukessays.com/essays/economics/descriptive research vs
analytical research economics essay.php
https://www.youtube.com/watch?v=UqtckUep840
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102
PLANNING OF RESEARCH
Unit Structure
2.0 Objectives
2.1 Introduction
2.2 Formulation of Research Problem
2.3 Research Design
2.4 Significance of Review of Literature
2.5 Hypothesis
2.6 Sampling
2.7 Summery
2.8 Exercise
2.9 Reference
2.0OBJECT IVES
After studying this unit the student will be able to 
Describe formulation of Research Problem
Understand the concept of Research design
Discuss significance of Review of Literature
Explain the concept of Hypothesis
Elucidate the concept of Sampling
2.1 INTRODUCTION
Understanding the research process is an important step towards
executing a thorough research or study. Let us examine the different
phases in research planning as well as the stages involved in a research
process.
2.2 FORMULATION O F RESEARCH PROBLEM
2.2.1 Meaning
Identification and formulation of a research problem is the first
step of the research process. It is the most challenging and difficult phase
of the research process.
A research problem is a question that a researcher w ants to answer
or a problem that a researcher wants to solve. In other words, researchmunotes.in
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11problem is an issues or a concern that an investigator / researcher presents
and justifies in a research study.
A research problem is the most important aspect of the research.
Researcher must spend time to refine and assess the research problem
before getting started with the research activities. A research question
must be straightforward, to the point and focused.
Example
Incorrect Research Problem: What are the eff ects of social media on
people?
Correct Research Problem: What effect does using Facebook everyday
have on teenagers?
In the above example, the first question is not specific enough to
capture accurate feedback. Nobody knows what social media researcher is
talking about and what ‘people’ (target population) researcher is referring
to.
2.2.2 Steps to Formulate of Research Problem
1)Identify the broad research area: The researcher begins research by
identifying a broad research area based on his/her interest , specialty,
profession, expertise, and knowledge. For example, a researcher
studying about Business Management can select areas like Marketing
Management, Human Resource Management, Organizational
Management, and Financial Management. These are the broade ra r e a s
that can be further subdivided into various research topics to figure out
marketing strategies.
2)Divide the broad area into sub areas: After the researcher chooses a
broad area to study, he/she need to narrow down to a specific topic that
is manage able and researchable. To do this, break down the broad area
into sub areas and choose a specific topic. For example, if your broad
area is Marketing Management it can be further divided into the
following subcategories:
Consumer Satisfaction
Marketing Mix
Consumer Relationship
Digital Marketing
3)Choose a sub area: It is not possible to study all the sub areas due to
time and money constraints. Thus, the researcher needs to choose one
subarea of interest and one that is manageable and feasible for
him/her. The area selected must have some research significance and
must be significant to the researcher’s research knowledge. Eg. A
researcher selects a sub area is ‘Consumer Satisfaction’.munotes.in
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124)Formulate research question/problem: After a specific sub area is
chose n, researcher needs to formulate research question/problem that
deems important for the research study. Many question/problem may
arise but narrow down and choose the most important and impact ful
question/problem. Eg. “A study on Consumer Satisfaction fro mA f t e r 
Sales Services provided by Samsung Company in Mumbai region”
5)Set research objectives: After research question/problem is framed,
researcher must draw a plan about the objectives of the research that
he/she need to explore. The objectives of the re search study help to
identify the research question/problem. There is a difference between
the research question/problem and the research objective. The
difference is the way they are written. Research question/problem
generally consists of an interrogativ e tone. On the other hand, the
research objectives are aim oriented. They include terms like to
examine, to investigate, to explore, and to find out. Example of
Research Objectives:
To investigate factors affecting consumer satisfaction from after 
salesservices provided by Samsung company
To find out various problems faced by consumers while availing
aftersales service of Samsung company
2.3 RESEARCH DESIGN
2.3.1 Meaning
After deciding the basic aspects of research project such as
formulating research p roblem, objectives of research, data requirement,
sample design etc. and before the commencement of work of research
project, the researcher has to prepare research design. Decisions relating to
what, where, when, how much, by what means concerning a resea rch
study constitute a research design.
Research design is a logical and systematic outline of research
project prepared for directing, guiding and controlling a research work. It
means to prepare detailed plan and procedure for the conduct of the
resear ch project. It acts as a broad outline of the research work and acts as
a master plan / blue print for the conduct of formal investigation. It is the
basic plan that guides researcher in the execution of research project
undertaken.
2.3.2 Elements of R esearch Design
1)Nature of the research and Objectives of study
2)Time period of research study
3)Universe and sample size of respondents
4)The location where the study would be conducted
5)The resources required to conduct the research
6)Type and source of research data required
7)Techniques of data collection and analysismunotes.in
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132.3.3 Need and Importance of Research Design
1)Provides Guidelines: Research design provides guidelines to the
researcher in respect of:
Time period of research work
Type and source of data to be col lected
Technique of data collection and analysis
Sampling design
Therefore, the researcher will be able to collect right data from the
right source at the right time. It also helps him to complete the research
within stipulated time.
2)Organizing Resources :Research design enables organizing of
resources required to carry on research activity. The resources required
are:
Funds
Equipment / instruments and materials
Manpower
Availability of right amount of resources facilitates smooth conduct of
research ac tivity. Research activity would be difficult to carry on
without availability of proper amount of resources.
3)Selection of Techniques of data collection and analysis: Research
design helps to select appropriate technique for data collection such as
Surve y or Interview
Observation
Experimentation
Internet
Library etc.
Research design also helps to select appropriate technique for data
analysis such as :
Measures of Central Tendency (Mean, Median, Mode)
Time Series (Simple Moving Average, Weighted Moving
Average)
Correlation Techniques etc.
4)Collection of Relevant Data: The research design indicates :
Area of research
Universe/Population of research
Sample Size etc.
Accordingly researcher can select right area of research and target
audience. He can deci de his universe/population from which samples
are selected to collect the relevant data.munotes.in
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145)Objectives of Research: Research design specifies objectives of
research. Research design provides right direction to the researcher to
carry on with research activ ity. This in turn will help to attend the
research objectives.
6)Monitoring of Expenditure: Research design includes allocation of
research budget for various research activities. There is proper control
over expenditure. Wastage of funds does not happen. The research is
successfully conducted with allocated funds.
7)Execution of Research Work: The research design indicates the start
time and completion time of research activity. Therefore, there is
timely execution of research work. If research design do es not indicate
the time frame, there is every possibility of research work getting
delayed and objectives may not be achieved.
8)Motivation to Research staff: A systematic research design motivates
the staff to collect the right data from the right source. Also due to
timely completion of research activity, the research staff may be
rewarded with monetary and non monetary incentives.
9)Improvement in Decision Making: Research design enables
researcher to collect right data from right source. Right data enab les to
take right decision. Wrong data may lead to misleading decision
making.
2.4 REVIEW OF LITERATURE
2.4.1 Meaning
The researcher must consult the available publications such as
books, journals, magazines, research reports and similar other publicat ions
before starting his/her own research activity. ROL refers to extensive
review of literature relating to research problem which researcher intends
to undertake. Such ROL provides good insides into research problems and
get familiar with previous resear ch studies undertaken.
2.4.2 Significance of Review of Literature (ROL)
1)Get background knowledge of research problem: A research
problem is a question that a researcher wants to answer or a problem
that a researcher wants to solve. ROL helps researcher to get
background knowledge of Research Problem.
2)Helps to identify gaps in research: Research gap refers to the areas
which are not explored in the past researches. ROL enables the
researcher to identify the gap in research, conflicts in previous studies,
open questions left from other research. The researcher can make an
attempt to fill this gap by undertaken research activity.munotes.in
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153)Help to formulate research hypotheses: Hypothesis is an assumption
made to explain certain fact or provide basis for further inv estigation.
It is tentative in nature and it may prove to be correct or incorrect. Past
studies or ROL helps researchers to frame hypothesis for his/her
current studies. The researcher collects data which may prove or
disprove the hypothesis. Based on the result of hypothesis testing a
conclusion can be drawn.
4)Get familiar with methodology adopted by other researchers:
Research methodology is the specific procedures or techniques used to
identify, select, process, and analyze information/data about a rese arch
problem. ROL enables researcher to get familiar with methodology
that is used by other researchers in their researches. Accordingly
he/she can decide his/her own methodology in terms or target
population, sample size, method and technique of data coll ection and
analysis and so on.
5)Prepare research design: Research design is a logical and systematic
outline of research project prepared for directing, guiding and
controlling a research work. With the help of ROL, a researcher can
prepare his/her researc h design. Research design keeps research work
on right track and help to complete research in time.
6)Prepare sample design: Asample design is the framework, or road
map, that serves as the basis for the selection of a survey sample. In a
research, it is n ot possible to collect data from entire
population/universe due to constraints of time, money and energy on
the part of researcher. So researcher needs to select samples from
population/universe of research. Sample selected must be true
representative of t he population/universe of research. ROL helps
researcher to prepare proper sample design.
7)Get familiar with data collection sources and data analysis
techniques: For the purpose of researcher primary or secondary or
both data can be used by a researcher. The primary data can be
collected by observation, survey or experiment method. Secondary
data can be collected from library, internet, reports etc. Collected data
needs to be analysed to draw conclusion out of it. Various statistical
tools can be used suc h as correlation, measures of central tendency and
so on for the purpose for data analysis. ROL facilitates to get familiar
with data collection sources and data analysis techniques used by other
researchers.
8)Understand findings of other researchers and t heir conclusions:
ROL helps researcher to understand findings of other researchers and
their conclusion. It can be basis for researcher’s own further research
activity.munotes.in
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169)To compile bibliography: Bibliography is a list of sources used in our
research. The main purpose of a bibliography entry is to give credit to
authors whose work researcher has consulted in his/her research. ROL
helps researcher to refer bibliography of others researchers to find out
more about the topic by exploring into their research.
10)Understand the structure of research report: Research report is a
written document containing key aspects of research project. After the
research work is completed, the findings along with recommendations
are presented in the form of research report to the authority for the
purpose of further decision making. So ROL enables researcher to
understand the structure of research report.
2.5 HYPOTHESIS
2.5.1 Meaning
Hypothesis is an assumption made by the researcher to explain
certain fact or provide basis for further investigation. It states what the
researcher thinks the outcome of the study will be. The researcher makes
hypothesis and collects data that either support the hypothesis or do not
support it. So the hypothesis may be proved to be correct or incor rect.
Hypotheses are essential to all research studies with the possible exception
of some descriptive studies whose purpose is to answer certain specific
questions.
Example A manager may hypothesize that salespersons who show the
highest job satisfac tion will be the most productive salespersons. Another
example, organizational researcher may believe that if workers’ attitudes
toward an organizational climate are changed in a positive direction, there
will be an increase in organizational effectiveness among these workers.
2.5.2 Definition
Webster’s Dictionary defines hypothesis as “ an unproved theory,
proposition, supposition etc. tentatively accepted to explain certain facts or
to provide a basis for further investigation, argument, etc.”
2.5.3 Fo rmulation of Hypothesis
1)Identification of Research Problem and its causes: The researcher
must identify the research problem which needs to be investigated.
Also he/she needs to identify cause of such problem. Eg. The research
problem could be “ Decline in Sales of Lux soap in Mumbai
Region”. The possible causes of such decline in sales could be:
Poor quality of the products
Higher price of the product
Ineffective promotion mix
Faulty distribution networkmunotes.in
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172)Formulate the Hypotheses: The researcher may underta ke extensive
Review of Literature (ROL) or discuss with expert or by his/her own
experience formulates the hypothesis. Eg. Hypotheses relating to the
above problem can be formulated as:
Sales are declining on account of poor quality of the products
Sales a re declining on account of higher price of the product
Sales are declining on account of ineffective promotion mix
Sales are declining on account of Faulty distribution network
3)Pilot Test the Hypotheses: The researcher may conduct pilot study to
test the hypothesis. Small sample respondents are selected and data is
collected from them to conduct the pilot study. All the hypotheses are
put to test. The pilot study may indicate the most probable cause of the
problem. This may help to select the best hypothes is for the purpose of
detailed investigation. Suppose the pilot study states that most
probable cause of problem is poor quality of the product.
4)Select the Best Hypothesis: After selecting the best hypothesis on the
basis of pilot study, the researcher pr oceeds for investigation of the
problem and find out the validity of the hypothesis. The researcher
may specify the null hypothesis and alternative hypothesis.
Null Hypothesis: It states that there is no relationship between two
or more variables. A resea rcher hopes to reject or disprove the null
hypothesis. Eg. There is no relationship between poor quality of
product and decline in sales.
Alternative Hypothesis: It states there is relationship between two
or more variables. Eg. There is relationship betw een poor quality
of product and decline in sales.
5)Conduct the Research: After formulating the final hypothesis, the
researcher proceeds to conduct the research. He/she may prepare
research design to conduct research in right direction. The researcher
collects data and analyse the same to draw conclusion. He may use T 
test, Z test, Chi Square, ANOVA, Correlation etc. tests for the purpose
for testing hypothesis.
6)Acceptance or Rejection of Hypothesis: After testing the hypothesis,
the researcher may reject the null hypothesis or the researcher may fail
to reject the null hypothesis. Generally, when the researcher rejects the
null hypothesis, the researcher may accept the alternative hypothesis.
At times, the alternative hypothesis may also be rejected.
2.5.4 Sources of Hypothesis
1)Intuition or Hunch: A person may get ideas to develop hypothesis
due to one’s own intuition or hunch. Ideas can strike like a flash. Eg.
The story of Laws of Gravitation propounded by Newton at the sight
of falling apple is the ca se of intuition.munotes.in
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182)Past Researches: Findings of the past researches done by others can
be used for framing the hypotheses. Eg. A researcher found in the past
researches that rise in rate of commission of salesman resulted in
increase in sales of the company. A researcher may use this finding to
formulate his research hypothesis as “Increase in rate of commission
of salesman leads to increase in sales.”
3)Consultations: The researcher can hold discussion with experts to
develop hypothesis. In academic research, the research students can
take help of a research guide who is expert in his/her own subject. In
applied (commercial) research, the researcher may take help of
marketing manager. In social research, the researcher may take help of
an NGO.
4)Observation: Hypothesis can be developed through own observation.
Eg. One can observe general pattern of buying behaviour in the
market, and develop a hypothesis such as “Educated customers prefer
braded items as compared to illiterate or less educated customers.”
5)Conti nuity of Research: Some researches are carried on for several
numbers of years. The research may be divided into different phases.
At each phase the researcher may get different findings based on
which he/she develops hypothesis for next phase.
6)Culture: While formulating a hypothesis for a problem, culture should
be studied. If a researcher wants to study trends towards female
education in a particular area, for this purpose he/she needs to study
traditions, family system, Norms, Values, region and educat ion system
of that area.
7)Theory: Logical deduction from the theory lead to new hypothesis.
The hypothesis must be valid, if the theory holds true. Eg. The theory
on human relations in management states that effective human
relations help to improve produc tivity. On the basis of this theory, a
hypothesis can be developed that “Effective management labour
relations facilitates higher productivity.”
8)Personal Experience: On the basis of personal experience, researcher
uses his mind and suggests hypothesis. Eg . A researcher experienced
poor services in the Government hospitals. He/she may develops a
hypothesis “Poor quality of services results into less footfall in
Government Hospitals.”
2.5.5 Importance
1)Helps to explore unknown facts: The hypothesis provides the
researcher with the most efficient instrument for exploring and
explaining the unknown facts. It stimulates the researcher for further
research studies.munotes.in
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192)Enables to prepare research design: The hypothesis helps in
preparing research design. It may sugge st research objectives, sample
design, data requirement, techniques of data collection, tests and tools
to analyse data etc.
3)Identifies need for data: A Hypothesis specifies the need of data i.e.
whether research will require primary data or secondary dat a.
Hypothesis would enable to collect required data. Without hypothesis
much useless data may be collected and important data would be
omitted.
4)Identifies sources of data: A Hypothesis also specifies the source of
data i.e. survey, experiment, observation , library, reports, internet etc.
Therefore, the researcher would consider only the relevant source of
data, which in turn would speed up the research activity.
5)Development of theory and principles: Hypothesis also facilitates
development of theory and principles. Eg. The theory of consumer
behaviour which presupposes that no two consumers think and behave
alike. Similarly, 14 Principles of Management by Henry Fayol, states
that practicing these principles in an organization, results into
increasing orga nizational efficiency.
6)Provides specific direction: When hypothesis is finalized a definite
and specific direction is provided to the research work. It makes way
to the progress of investigation. In the absence of hypothesis it
becomes extremely difficult to focus on research problem.
7)Prevents blind research: Hypothesis lights up the path of research. It
distinguishes between scientific and unscientific inputs. It acts as a
guide. Accuracy and precision is possible through hypothesis.
Therefore, hypothes is prevents blind research.
8)Economical: Developing hypothesis in business research is
economical. It saves time, money and energy of a researcher because it
guides the researcher in the right direction. Hypothesis provides the
basis for proper data collec tion. Relevant and correct information
collected by a researcher through properly formulated hypothesis
proves resource saving.
2.5.6 Types of Hypothesis
1)Simple Hypothesis: It reflects the relationship between one dependent
variables (DV) and one indepen dent variable (IDV).
Examples:
Higher the unemployment (IDV), higher would be the rate of
crime (DV) in societymunotes.in
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20Lower the use of fertilizers (IDV), lower would be agricultural
productivity (DV).
Higher the poverty (IDV) in the society, higher would be the rate
of crimes (DV).
2)Complex Hypothesis: It reflects the relationship between two or more
dependent variables and two or more independent variables.
Examples:
Higher the poverty (IDV) leads to higher rate of illiteracy (DV) in
the society, higher would be the rate of crime (DV).
Lower use of fertilizer (IDV) and modern equipments (IDV), lower
would be the agricultural productivity (DV)
3)Directional Hypothesis: A directional hypothesis is a prediction made
by a researcher regarding a positive or negative ch ange, relationship,
or difference between two variables of a population. This prediction is
typically based on past research, accepted theory, extensive
experience, or literature on the topic. For example “There will be a
positive relationship between ex tra coaching and academic
achievement”
4)NonDirectional Hypothesis: This form of hypothesis is used in
studies where there is no sufficient past research available on which
predication can be made about relation between variables. It does not
stipulate t he direction of the relationship. It is a statement that a
relationship exists between two variables, without predicting the exact
nature (direction) of the relationship. Eg. “Teacher –student
relationship influence student’s learning.”
5)Null Hypothes is:This is a hypothesis that proposes no
relationship or difference between two variables. It involves a
statement that says there is no relationship between two groups that the
researcher compares on a certain variable. It is denoted by “H 0”.
Example –
There is no relation between poverty and crime in a society.
‘There is no difference in the academic performance of high school
students who participate in extracurricular activities and those who
do not participate in such activities’
6)Alternati ve Hypothesis: This hypothesis proposes a relationship
between two or more variables. Alternative hypothesis is denoted by
“H1”. Example –
There is relation between poverty and crime in a society.
‘There is difference in the academic performance of high school
students who participate in extracurricular activities and those who
do not participate in such activities’munotes.in
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217)Causal Hypothesis: Causal hypotheses propose a cause and effect
interaction between two or more variables. This hypothesis predicts
the effe ct of independent variable on the dependent variable. Eg. ‘High
school students who participate in extracurricular activities spend
less time studying which leads to a low grades.’
8)Associative Hypothesis: These hypotheses aim to determine if
relationships exist between a set of variables. Do not indicate cause
and effect.
9)Testable Hypothesis: These hypotheses predict relationship between
the independent variable and the dependent variable. These variables
are testable or measurable.
2.6 SA MPLING
2.6.1 Meaning
Sampling is a technique of selecting a subset (part) of the
population to make statistical inferences (conclusion) from them and
estimate characteristics of the whole population. Different sampling
methods are widely used by researche rs in market research so that they do
not need to research the entire population to collect data. It is also a time 
convenient and a cost effective method and hence forms the basis of
anyresearch design .
In other words, Sampling means the process of selecting a part of
the population. A population is a group of people that is studied in a
research. It is difficult for a researcher to study the whole population due
to limited resources such as time, cost and energy. Hence, the researcher
selects a part of the population for his study, rather than studying whole
population. This process is known as sampling. It makes the r esearch
activity manageable and convenient for the research.
2.6.2 Definition
According to Bogrdus, “Sampling is the selection of certain percentage
of a group of items according to a predetermined plan.”
2.6.3 Significance of Sampling
1)Time Saving: Since using a sample reduces the number of people that
have to be reached out to, it reduces time. Sampling helps to save time
in respect of data collection and its analysis. The data can be collected
at faster rate, so also data analysis. Therefore, the resea rcher can get
quick research results and accordingly can take timely action.
2)Economical: Since using a sample reduces the number of people that
have to be reached out to, it also reduces cost. For any research,
availability of funds is a constraint. A sma ller sample requires less
funds not only for data collection but also for processing and
interpretation of data.munotes.in
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223)Reduced resource deployment: It is obvious that if the number of
people involved in a research study is much lower due to the sample,
the reso urces required are also much less. The workforce needed to
research the sample is much less than the workforce needed to study
the whole population.
4)Convenient: Sampling offers convenient to the researcher to collect
the data. The work of data collection becomes easy, quick and
economical. A researcher can complete his research project in time.
5)Quality of Research Work: The quality of research work may be
improved due to sampling. The field staff will get sufficient time to
collect the data from sample r espondents. They need not to rush
through the collection of data. Also, data analysis staff gets sufficient
time for data analysis purpose. Therefore, overall quality of research
work improves.
6)Reduce Complexities: Sampling helps to reduce complexities i n
research work. If a limited sample is used, then fewer respondents are
required to collect data. As a result, the researcher may require less
time for editing, coding and interpretation of data. Therefore, analysis
can be quick and without complexities.
7)Motivation to Research Staff: Limited sample size brings relief to
the research staff. They get motivated to collect the right information.
This is because they get sufficient time for collection and analysis of
data. They may also get higher rewards due to good quality research
work.
8)Detailed Information: Due to sampling, the researcher can collect
detailed information from the sample respondents. They can ask more
questions than questions in questionnaire. Since there are lesser
respondents, the data collected from a sample is intense and thorough.
More time and effort is given to each respondent rather than having to
collect data from a lot of people.
9)Infinite Population: If the population is too larger then the sampling
method is the best way to fin d out solution.
10)Accuracy of data: Since the sample is indicative of the population,
the data collected is accurate. Also, since the respondent is willing to
participate, the survey dropout rate is much lower, which increases the
validity and accuracy of the data.munotes.in
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232.6.4 Methods of Sampling
2.6.5 Probability Sampling Method
Probability sampling is amethod of deriving a sample where the
objects are selected from a population based on the theory of probability.
This method includes everyone in the population, and everyone has an
equal chance of being selected. Hence, there is no bias whatsoever in this
type of sample. Each person in the population can subsequently be a part
of the research. The selection criteria are decided at the outset of the
market research study and form an important component of research.
The various probability sampling methods are discussed as below:
1)Simple Random Sampling: This is the most popular method which is
normally followed to collect research data. This technique provides
every member an equal chance of being selected in the sample. The
members are selected randomly an d purely by chance. There are two
submethods:
Lottery Method: Where each member is given a number and then
the numbers are mixed and by drawing of lots, the sample is
selected.
Random Tables: The members are given numbers and the
numbers are placed in rows. The sample is selected from rows at
random.munotes.in
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24
2)Systematic Sampling: Systematic sampling is a sampling method
where the researcher chooses respondents at equal intervals from a
population. Every member of the population is listed with a number,
butinstead of randomly generating numbers, individuals are chosen at
regular intervals. Example : If the total population is 100 and the
sample size is 10. Each respondent is given a number from 1 to100. A
certain number is selected say no. 3. So number cons ist of 3, 13, 23,
33, 43, 63, 73, 83, 93 will be selected as sample.
3)Stratified Random Sampling: This sampling method is appropriate
when the population has mixed characteristics, and researcher wants to
ensure that every characteristic is proportiona lly represented in the
sample. Researcher divides the population into subgroups (called
strata) based on the relevant characteristic (e.g. gender, age range,
income bracket, job role). The strata are formed by researcher. Then
he/she uses random or system atic sampling to select a sample from
each subgroup. Example The company has 800 female employees
and 200 male employees. Researcher wants to ensure that the sample
reflects the gender balance of the company, so he/she sorts the
population into two strat a based on gender. Then researcher uses
random sampling on each group, selecting 80 women and 20 men,
which give researcher a representative sample of 100 people.munotes.in
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25
4)Cluster Sampling: Cluster sampling also involves dividing the
population into subgroups, but each subgroup should have similar
characteristics to the whole sample. The clusters are naturally formed.
Instead of sampling individuals from each subgroup, researcher
randomly selects entire subgroups. If the clusters themselves are large,
research er can select sample from each cluster using simple random or
systematic sampling method. This method is good for dealing with
large and dispersed populations, but there is more risk of error in the
sample, as there could be substantial differences between clusters. It’s
difficult to guarantee that the sampled clusters are really representative
of the whole population. Example The Company has offices in 10
cities across the country (all with roughly the same number of
employees in similar roles). Research er doesn’t have the capacity to
travel to every office to collect data, so he/she uses random sampling
to select 3 offices –these are the clusters.
2.6.6 Non Probability Sampling Method
Nonprobability sampling is defined as a sampling technique in whi ch
the researcher selects samples based on the subjective judgment of the
researcher rather than random selection. It is a less stringent method.
This sampling method depends heavily on the expertise of the
researchers. It is carried out by observation, an d researchers use it
widely for qualitative research.munotes.in
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261)Convenient Sampling: It is a type of where samples are selected from
the population only because they are conveniently avai lable to the
researcher. Only those members are selected which are easily
accessible to the researcher. Eg. A researcher may visit a college or a
university and get questionnaires filled in by volunteer students.
Similarly, a researcher may stand in a mark et and interview the
volunteer persons.
Ideally, in research, it is good to test a sample that represents the
population. But, in some research, the population is too large to
examine. It is one of the reasons why researchers rely on convenience
sampling , which is the most common non probability sampling
method, because of its speed, cost effectiveness, and ease of
availability of the sample.
2)Judgment or Purposive Sampling: In this method of sampling
researchers select the samples based purely on the researcher’s
knowledge and credibility. In other words, researchers choose only
those people who they deem fit to participate in the research
study. Judgmental or purposive sampling is not a scientific method of
sampling, and the downside to this sampling technique is that the
preconceived notions of a researcher can influence the results. Thus,
this research technique involves a high amount of ambiguity.
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273)Quota Sampling: Under this method, the researcher allocates certain
quota to certain groups under st udy. The quotas may differ from each
area depending upon certain factors like age, occupation, income etc.
Eg. A researcher studying the newspaper reading habits of college
students may select 10 colleges for data collection. He may fix quota
for each coll ege based on certain criteria. He may select 100 students
from one college, may be because the number of students is more in
that college; and he may select only 20 students from another college
because of less number of students in that college.
4)Snow Ball Sampling: Snowball sampling helps researchers find a
sample when they are difficult to locate. Researchers use this
technique when the sample size is small and not easily available. This
sampling system works like the referral program. It is a sampli ng
design in which respondents selected earlier are asked to identify other
sample members. Eg. To find out Mercedez Benz car owners in the
city like Mumbai. In this case, researcher may locate one Mercedez
Benz owner and collect the names of 2 3 other Mer cedez Benz
owners.
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282.6.7 Factors determining sample size
1)Area of Research: The number of sample respondents depends on the
area of research. If the research is conducted at national level, it may
require more number of respondent. If the research i s conducted at
local level, it may require less number of respondents.
2)Availability of Funds: Generally, the researcher may be constrained
by the limitation of funds to conduct the research. Therefore, when the
researcher has limited amount of funds allo cated to the research
activity, the sample size would be lesser as compared to when the
researcher has larger amount of funds.
3)Availability of Manpower: The researcher may require manpower to
conduct surveys, interviews or for conducting experiments,
obser vation etc. Eg. If the researcher has a good number of filed staff
to conduct interviews, he may select the larger sample size of
respondents and vice versa.
4)Time Frame: The sample size may depend on the time frame of
research. If the researcher has lot of time available to conduct the
research, he may select a large sample size of respondents and vice 
versa.
5)Nature of Research: The nature of research may influence the sample
size of respondents. Eg. In case of academic research, the researcher
may be cons trained with the limitations of funds, and therefore, he
may select a smaller sample size. However, in the case of census
survey of population, the sample size will be the entire population of
the country.
6)Method of Sampling: The method of sampling may inf luence the
sample size of respondents. Eg. If convenience sampling method is
used, the researcher may consider a smaller sample size to obtain
responses. However, in case of stratified sampling or cluster sampling,
the researcher needs to select a larger s ample size of respondents.
7)Method / Sources of Data Collection: The method of data collection
may influence the sample size of respondents. Eg. If researcher
collects data through interviews, he may select a larger sample size of
respondents. However, if the researcher adopts observation method, he
may consider a smaller sample size for the purpose of observation.
8)Judgment of the Researcher: At times, the researcher may use his
judgement in deciding in the sample size. He may consider a smaller
sample size , if he is confident in getting the adequate data from a
smaller sample size. However, if the researcher feels that he needs to
select a larger sample to collect responses, he may select a larger
sample size.munotes.in
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292.7 SUMMARY
This unit talks about formulatio n of research problems, which is a
first step in research activity. Proper formulation of research problems
enables researchers to carry on research activities accurately and
researchers understand what kind of research data is required to collect
and achi eve research objectives.
Another part of this unit is about Research Design. Research
design is a plan of research. It enables us to plan the various activities of
research such as sampling method, data collection and analysis method,
resources required etc. Research design enables us to start and end the
research on time. Delayed research may not hold any importance.
Next part of this unit Review of Literature. It refers to the
previously done research. This provides insight to the researcher and
provid es direction as to how he can carry on his/her research activity.
Hypothesis is another part of this unit. It refers to the assumption
made by the researcher, which he/she tries to cross check after collecting
the data. It can be proved to be correct or i ncorrect. That the researcher
can confirm only after collecting data from the respondents.
Sampling is the last part of this unit. Since the researcher cannot
collect data from the entire population/universe under study, he/she can
select samples by adop ting different methods of sampling. Research data
is collected from these samples and the result of it is generalized on the
entire population / universe under study.
2.8 EXERCISE
FILL IN THE BLANKS
1._____________ is a question that a researcher wants to answer or a
problem that a researcher wants to solve
A)Hypothesis B) Data Analysis
C) Research Problem D) Research Report
2.___________ is a logical and systematic outline of research project
prepared for directing, guiding and controlling a research work
A)Universe / Population B) Research Design
C) Hypothesis Testing D) Review of Literature
3.Review of Literature enables the researcher ___________
A)To pirate the research software
B) To undertake plagiarism
C)To identify gaps in research
D) To collect data from entire populationmunotes.in
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304._____________ hypothesis proposes no relationship or no
difference between two variables.
A)Simple B) Associative C) Alternative D) Null
5.___________ is one of the probability meth ods of sampling
A)Cluster Sampling B) Quota Sampling
C) Judgemental Sampling D) Snow Ball Sampling
TRUE OR FALSE
1.“A study on E Commerce” is a correctly formulated research
problem. FALSE
2.Research design contains details regarding nature of the res earch and
objectives of study, time period of research study, universe and sample
size of respondents, type and source of research data required and
techniques of data collection and analysis. TRUE
3.Sampling refers to consult the available publications such as books,
journals, magazines, research reports and similar other publications
before starting his/her own research activity. FALSE
4.Intuition is one of the sources of generating hypothesis. TRUE
5.Directional hypothesis is used in studies where there is no sufficient
past research available on which predication can be made about
relation between variables. FALSE
6.Snow ball sampling is a sampling method where the researcher
chooses respondents at equal intervals from a population. FALSE
MATCH THE PAIRS
Group A Group B
6)Review of Literature g)Outline of the research work
7)Research Design h)Helps to get familiar with previous
research studies undertaken
8)Alternative Hypothesis i)NonProbability Sampling Method
9)Judgement Sampling j)Denoted as “H 1”
(1–b, 2 –a, 3–d, 4 –c)
ANSWER IN BRIEF
5)What is Review of Literature? Elucidate its significance.
6)How to formulate research hypotheses?
7)Describe the different sources of generating hypotheses.
8)Highlight the importance of hypothesis in research.
9)Briefly explain types of hypothesis.
10)Define the term ‘Sampling’. Explain its significance.munotes.in
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3111)Discuss various methods of sampling.
12)What are the factors determine sample size?
13)Write a note on:
Formulation of Research Problem
Research Design
2.9 REFERENCES
https://www.youtube.com/watch?v=UqtckUep840
https://www.slideshare.net/maheswarijaikumar/a research problem
https://www.questionpro.com/blog/research problem/
https://www.researchgate.net/publication/325846748_FORMULATIN
G_AND_TESTIN G_HYPOTHESIS
https://www.questionpro.com/blog/non probability sampling/
https://www.scribbr.com/methodology/sampl ingmethods/
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32Module II
RESEARCH PROCESS
3
STAGES IN RESEARCH PROCESS
Unit Structure
3.0 Objectives
3.1 Introduction
3.2 Stages in Research Process
3.3 Primary Data
3.4 Methods of Collecting Primary Data
3.5 Summary
3.6 Exercise
3.7Reference
3.0 OBJECTIVES
After going through this unit the learner will understand
1. Various Stages in Research Process
2. Primary data
3. Different sources of collecting Primary Data
4. Limitations of Primary Data
3.1 INTRODUCTION
Research refers t othe systematic investigation into and study of
materials and sources in order to establish facts and reach new
conclusions. To attain correct results Research has to be done with a
predefined process. In this unit we will learn What are different stages in
Research Process, How Primary Data is collected
3.2 STAGES IN RESEARCH PROCESS
3.2.1 MEANING
Each and every researcher needs to follow appropriate research
process for successful completion of his or her research project. A
researcher who is conducti ng scientific research needs to follow a
systematic process to study the research problem and to arrive at a
conclusion. The scientific research process includes a sequence of various
steps that needs to be followed while undertaking the research project.
Every research problem is unique and it requires research work to bemunotes.in
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33carried out accordingly. Following different steps to be followed in the
research process.
I] Identifying and selection of research problem:
The most important step in the research pr ocess is to identify and
select research problem, it is often said a well defined problem is half
solved. High degree of intellectual work is needed to identify and define
the research problem. A properly defined research problem will help
researcher to collect reliable data to solve the research problem and in that
case he will be in a better position to arrive at a suitable conclusion based
on Analysis of data.
Following are some of the Essentials of a good research problem
1.Researchable : the identifi ed research problem can be studied through
collection and Analysis of data
2.Understandable : The research problem should be understandable it
should be well formulated and logically structured
3.Ethical : The selected research problem should not harm the res earcher
respondents and Society. You should not create any embarrassment
every of the stakeholder in the world in research process
4.Purposeful : The research problem should be defined in such a way
that after concluding this study it should be able to solv e the situation.
5.Manageable : the research problem should be manageable the
researcher should take care that the problem should be within limits of
his skills resources and time.
II] Review of literature:
Review of literature refers to study of available knowledge in
respect of research problem. A researcher can study Various publications
such as journals books research reports other published matter particularly
the researcher should go to the similar research study that were conducted
previously. Litera ture review is important because it is the duty of research
to find out what study has been already done literature review will help the
researcher to find out gaps in earlier study. On the basis of those gaps
researcher can formulate his Research Design L iterature review on both
matic as well as methodological direction to the researcher.
III] Formulation of the hypothesis & Research Design
Once the researcher has clearly defined the research problem and
has made in depth literature review he needs to fo rmulate Research
Design for his study. The researcher also need to formulate hypothesis for
his research.
This is a tentative assumption made to test its logical and empirical
consequences. The hypothesis should be formulated on the basis of index
knowle dge of the research problem. A well defined hypothesis will clearlymunotes.in
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34identify the kind of data required by the researcher to conduct the study
which will help him to create a suitable Research Design.
Research Design is a systematic and logical plan prepar ed to
conduct a research study we can call it as a blueprint for research study.
The Research Design will include guidelines in respect of collection,
measurement and analysis of data required for the research study.
IV] Sampling Design :
A researcher nee ds to collect Information for his study however it
is not possible to collect information from each and every member of the
universe hence he needs to select sample for data collection. The research
needs to select an appropriate sampling method which is s uitable for the
study. The selected sample must be representative of the universe. Its size
must be flexible and sufficient enough to provide required information
which can be analysed and used to test the hypothesis.
V] Designing Questionnaire :
The res earcher needs to collect primary data for his study. He
cannot rely only on secondary data. Primary data can be collected through
various sources however the most commonly used is Questionnaire.
Questionnaire is a list of questions that will be asked by re search to the
respondents for Collection of data. While designing questionnaire
researcher need to consider various aspects such as what type of
information is needed, what type of technique will be used for conducting
the research and he also need to take care regarding proper wording and
sequence of the questions.
VI] Collection of data :
The researchers need to collect all relevant information in respect
of his research problem as per Research Design through various sources.
He can use primary data an d secondary data for purpose of research.
While collecting data researcher need to consider that information
collected is up todate and free from any bias. the information must be
complete in all aspects and the information must be relevant to the
resear ch problem.
VII] Processing and analysing data :
The researcher collects data from primary as well as secondary
sources however the data collected is in raw form and it needs to be
processed for further analysis.
Processing of data in hall editing, codin g, classification, and
tabulation of data. Editing of data refers to removing unwanted and
irrelevant information it is necessary to check errors and omissions in data
collection. coding refers to assigning different codes to the collected data
which helps in further processing of the information classification of data
refers to grouping of data under different categories and tabulation of datamunotes.in
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35involves transferring all classified data into tabular form tabulation of data
helps in analysis and interpretatio n of data.
Once data is organised the researcher needs to analyse the data.
Analysis of data is very crucial as it tries to establish relationship between
information and research problem. Once that relationship is established
interpretation of data and f inding out logical conclusions of study is
possible.
VII] Hypothesis Testing :
Once analysis and interpretation of data is over the researcher must
test hypothesis. hypothesis testing is necessary because researcher need to
confirm whether the finding o f the research supports the hypothesis or
provides a contrary picture. Researcher may apply various tests such as
Chisquare test, F test, t test for testing the hypothesis. Once hypothesis is
tested its result will either lead its acceptance or its reject ion.
IX] Preparation of Research Report :
The researcher must prepare a research report which includes all the
findings and conclusions of his study. The report can be divided into three
parts.
1.Preliminary Content. : This includes preface, table of conte nts and all
other related authorisations and declarations in respect of the Research
report.
2.Main body This includes introduction, literature review, research
methodology, data analysis, conclusion and recommendations.
3.Appendix this will include all the annexure bibliography and other
supportive documents related to the research.
3.3 PRIMARY DATA
In statistical analysis, collection of data plays a significant part.
The method of collecting information is divided into two different
sections, namely primary data and secondary data. In this process, the
primary data is assembling data or information for the first time, whereas
the secondary data is the data that has already been gathered or collected
by others.
3.3.1 Definition of Primary Data:
Prima ry data is the data that is collected for the first time through
personal experiences or evidence, particularly for research. It is also
described as raw data or first hand information
3.3.2 Characteristics of Primary Data
Following is list of characteris tics of Primary Data.
1.Primary data is original datamunotes.in
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362.Collection of primary data is an expensive exercise
3.Collection of primary data is a time consuming
4.Data Lake to be collected considering research problem
5.Primary data is collected from relevant responden ts
6.There are several methods of collecting primary data such as
Survey, Observation experimentation etc.
7.Primary data need to be processed and analysed before its use.
8.Primary data is considered to be basic input in research study.
3.4 METHODS OF COLLECT ING PRIMARY DATA
Primary data is collected by researchers by interacting with or
observing the respondents; it can be collected through various methods
such as survey, interview, observation and experimentation.
1.Survey
2.Interview
3.Observation
4.Experimentatio n
3.4.1. Survey Method :
The Survey method is the technique of gathering data by asking
questions to people who are thought to have desired information. This data
is comprehensive information gathered from a target audience about a
specific topic to condu ct research. Survey can be a Census or Sample
Survey
Census : In case of Census Survey the entire universe is contacted for
collecting information.
Sample Survey : In case of sample survey information is collected from
selected respondents of the univers e.
Methods of Survey:
The researcher can apply different methods of Survey based on the
research problem, No of respondents from whom information to be
collected, time available to the researcher and his financial limitations.
Today technology available with the researcher and respondents also plays
a crucial role in selecting the survey method. Following are different
methods of survey.
1.Interview : In this method researcher meets respondents personally
and asks questions regarding his research problem an d collects the
relevant information. Which is the most traditional, expensive and
most effective method of collecting data.
2.Telephonic Survey : In this method the researcher does not meet
respondents personally. However the survey is conducted through
telephonic discussions. The researcher asks various questions to the
respondents on telephone and collects the required information.munotes.in
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373.Mail Survey : This is another method of Survey it is generally used
when the number of respondents is very high and there i sa
geographical challenge for a researcher. In this method a
questionnaire is prepared and sent to the respondents via mail or it can
be advertised in newspapers and magazines and respondents are asked
to fill in the information and send it back to the r esearcher.
4.Online Surveys : Now a days this method of collecting information is
gathering momentum today we have high penetration of internet
services in India particularly in urban and semi urban areas, in this
method the researcher can collect informatio n from respondents by
sending the Google Form or Microsoft from through email or other
communication applications such as WhatsApp or Telegram.
Each and every method has its own Advantages and disadvantages.
Following are Advantages and disadvantages of S urvey
3.4.2. Advantages of Survey Method
1.Reliable and Detailed Information : Information collected through
survey is more reliable. The researcher collects information from
respondents directly sold is assumed to be more reliable and correct
however accur acy of the information depends upon the type of
questions the survey method and the respondents bias towards the
research problem
2.Versatile : This method is most versatile. A researcher can restructure
or modify the questions according to the responses he has received. He
can delete certain questions according to the situation, he may ask
questions to the respondents in the different languages to obtain
responses from the respondents.
3.Personal touch : This method allows the researcher to create personal
relationship with respondents which help the researcher to obtain
candid responses from the respondents on the questions which
otherwise could have been avoided by the respondent.
4.Cost effective : This method is cost effective in terms of quality of
inform ation obtained through this method.
3.4.3. Disadvantages of Survey Method.
1.Time consuming : This method is time consuming, a lot of time is
needed to prepare a questionnaire, to take appointment of the
respondent and obtain responses from him.
2.Personal Bias : The quality of information obtained from this
particular method can be affected due to personal bias of interviewer
as well as respondent. The respondent may not provide correct
information while answering the questions and at the same time
intervi ewer / researcher may bypass or twist the questions which
prohibit respondents from providing the correct information.munotes.in
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383.Expensive : Survey method is expensive and it is difficult for a
researcher with limited financial strength.
3.4.4. Interview Method :
In the case of an interview the researcher or interviewer interacts
with respondents personally by meeting the respondent. In this method
there is face toface interaction between researcher and the respondent. It
is also called a Personal Interview. In thi s method the interviewer asks
questions to the respondent and collects information through its answer
given by the respondent. There are various types of personal interviews.
1.Structured Interview In this type of interview the interviewer uses a
set of p redetermined questions and highly standardized techniques of
recording.
2.Unstructured Interview In this method interviewer does not follow
a system of predetermined questions and standardized techniques of
recording information and it is fully based on f lexibility and
requirements.
3.Clinical Interview This type of interview is concerned with broad
underlying feelings or motivations or with the course of an
individual’s life experience.
4.Nondirective Interview In this type the interviewer simply to
encourage the respondent to talk about the topic with a bare minimum
of direct questioning.
5.Focused Interview In this type of interview the task of the
interviewer is to confine the respondent to discuss about given
experience to them and its effects.
Nowadays such interviews can be taken through video
conferencing platforms such as Zoom, Google Meet or Microsoft Teams.
3.4.5. Advantages of Interview
●Higher response rate.
●When the interviewees and respondents are face toface, there is a way
to adapt the questions if this is not understood.
●More complete answers can be obtained if there is doubt on both sides
or a particular information is detected that is remarkable.
●The researcher has an opportunity to detect and analyze the
interviewee’s body language a t the time of asking the questions and
taking notes about it.munotes.in
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393.4.6. Disadvantages of Interview
●They are time consuming and extremely expensive.
●They can generate distrust on the part of the interviewee, since they
may be self conscious and not answer tr uthfully.
●Contacting the interviewees can be a real headache, either scheduling
an appointment in workplaces or going from house to house and not
finding anyone.
3.4.7 Observation Method :
This is another method of collecting data, in this method the
researcher does not Ask any question to the respondent but observes the
behaviour of respondents. The observation Method can be defined as
“Observation is a technique that involves systematically selecting,
watching, listening, reading, touching, and recordin g behavior and
characteristics of living beings, objects, or phenomena.”
3.4.8. Advantages of Observation Method
1.No Respondent Bias : There is no any respondent bias involved in
collecting data. in this method behaviour of respondents is observed
and res pondents may not be aware that they are being observed hence
they behave naturally without any bias.
2.Accurate and Reliable : The information collected through this
method is accurate and reliable as it is collected without any bias and it
is collected at the point of action or reaction of the respondent.
3.4.9. Disadvantages of Observation Method
1.Time Consuming : It is time consuming method for collection of data,
researchers need to observe behaviour of all respondents patiently.
2.Expensive : It is an expe nsive method of Data Collection as a
researcher may have to appoint trained staff for observing behaviour of
respondents.
3.Non Verbal Method : It is a nonverbal method of Data Collection, in
depth collection of information like interview method is not pos sible
through this method.
3.4.10. Experimentation Method :
Experimentation method of data collection is normally followed in
the field of science. In this method research study cause and effect
relationship between two or more variables through experim ents.
An experiment is a structured study where the researchers attempt
to understand the causes, effects, and processes involved in a particular
process. This data collection method is usually controlled by the
researcher, who determines which subject is used, how they are grouped
and the treatment they receive.munotes.in
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403.4.11. Advantages of Experimentation Method
1.Researcher have full control on the experiment
2.Researchers can obtain reliable and accurate information through
experiments.
3.It eliminates any kind of bias in Collection of data.
3.4.12. Disadvantages of Experimentation Method
1.Expensive method of Data Collection
2.It could be time consuming
3.Small error could result into failure of experi ment
3.4.13. Schedules
The researcher may use a schedule while collecting data from
interview or observation. Schedule is an instrument used to collect data
from the respondents Schedule contains questions, statements (on which
respondents are expected to give their opinion) It provides blank
spaces/tables to the respondents to fill up their responses. Schedule is
important as it help researcher to attain objectivity by reminding him
different aspects to be observed.
The features of schedules are :
1.The sc hedule is presented by the interviewer.
2.The questions are asked and the answers are noted down by him.
3.The list of questions is a more formal document, it need not be
attractive.
4.The schedule can be used in a very narrow sphere of social research.
There are several kinds of schedule.
1.Rating Schedules : It is a schedule which contains positive and
negative statements of opinion on the phenomenon. The respondents
are to express their opinions, preferences etc, respondents over
statements on the phenomenon studied and schedule is used to record
their responses.
2.Documents Schedules : are used to collect data/information from
recorded evidences and/or case histories. Here the blanks, functional
issues related blanks and the like to be filled up from records an d
documents are present.
3.Survey Schedules : Survey schedules are like questionnaires, it is a
list of questions that need to be answered by respondents.
4.Observation Schedules : Observation schedules are schedules used
when the observational method of data collection is used.munotes.in
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413.4.14. LIMITATIONS OF PRIMARY DATA
1.Expensive : Primary data collection methods are expensive
comparing it to secondary data. It requires appointment and training
of staff for collecting information through Interviews, surveys o r
observation. It also requires sophisticated equipments for conducting
experiments. However such expenses are not required when secondary
data is used by researcher.
2.Time consuming : Collecting data through primary sources could be
timeconsuming as it re quires time to collect information from each
and every respondent, observe the sample as well as experiments.
3.Bias : Reliability and accuracy of primary data could be affected due
to bias of researcher or respondent. Respondents may provide fake
informatio n to the researcher regarding sensitive topics. Interviewer /
researcher may also not take sufficient efforts to collect information
from the respondents.
4.Processing of data : the information collected from respondent need
to be edited, coded, classified and tabulated before its analysis only
after properly analysing the data useful inferences can be drawn.
5.Sampling Error : While collecting information it may not be possible
to collect information from all the respondents of the Universe.
Researcher may have to collect information from sample i.e. selected
respondents from the entire population, sample selection could be
wrong which may lead to collection of wrong information and wrong
conclusions from the research.
3.5. SUMMARY
This module has discuss ed the Research Process thoroughly, the
unit also discusses Primary Data its Features Advantages and
Disadvantages. It also discusses various methods of collecting primary
data thoroughly. The unit has also provided Limitations of Primary Data.
However a r esearcher may not rely only on Primary Data, he may have to
use secondary data as well. It is discussed in the next unit
3.6 EXERCISE
1.Describe Stages in Research Process
2.Explain Importance of Primary Data
3.Explain methods of collecting primary data
4.Explai n limitations of primary data
5.Write Short Notes on
a.Interview
b.Schedule
c.Observation Method
d.Experimentation Method
e.Survey Methodmunotes.in
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42State following statements are True or False
1.The research problem should be clearly defined
2.Literature review to provide good ins ight into research problem
3.Tabulation of data helps in analysis and interpretation of data
4.Collecting Primary data is inexpensive
5.There are no disadvantages of experimentation
(True 1,2,3, False 4,5)
3.7 REFERENCE
Research Methodology : Michale Vaz , Aurora Vaz : Manan Prakashan
Research Methodology Methods and Techniques : C. R. Kothari, New
Age International Publishers
Research Methodology : R Panneerselvam, PHL L:earning
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434
SECONDARY DATA
Unit Structure
4.0 Ob jectives
4.1 Introduction
4.2 Secondary Data
4.3 Methods / Sources of Secondary Data
4.4 Factors Influencing Choice of Method of Data Collection
4.5 Questionnaire
4.6 Summary
4.7 Exercise
4.8 Reference
4.0OBJECTIVES
After going through this unit the learner will understand
1. What is Secondary Data ?
2. What are different methods of collecting Secondary Data ?
3. What are limitations of collecting secondary data ?
4. Factors influencing selecting methods of collecting data
5. The process of Questionn aire
4.1 INTRODUCTION
In earlier unit we learned about primary data. However the
researcher also needs to look into Secondary Data. The researcher should
go through all published material regarding his area of study, that
published material such as Journ al, Magazines, Research Papers,
Websites, books etc is called Secondary data. Based on available
secondary data the researcher will identify the area in which he can
conduct research and collect necessary primary data.
4.2 SECONDARY DATA
This data is rea dily available for researchers. It is available from
published sources such as newspaper, magazines, research journals,
research papers etc. Generally any researcher makes an attempt to obtain
information through secondary data and if secondary data is ins ufficient or
redundant the researcher will try to obtain primary data.munotes.in
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444.2.1 Features of Secondary Data
1.Readily available data : Secondary data is collected from published
as well as unpublished sources. Secondary data is available internally
(from own r ecords, accounts etc) or externally. It is already collected,
processed and published by other researcher.
2.Quickly collectible : Secondary data is readily available hence it is
easy to collect. The researcher can easily collect secondary data as
compared t o primary data.
3.Less time consuming and Less Expensive : Secondary data is easy to
collect as it is readily available hence it can be collected in less time. It
is also less expensive to coolest secondary data.
4.Comprehensive : Secondary data provide quanti tative data.
Information available through secondary data is huge. Secondary data
is available for almost all subjects.
5.Relevance : Secondary data is available for almost all subjects.
However the secondary data available may not be related with the
resear ch topic hence the researcher need to evaluate the available
secondary data.
4.2.2 Advantages of Secondary Data
Followings are advantages of Secondary Data.
1.Less Processing of Data : Secondary data is already processed earlier
hence it requires less proce ssing of data. It becomes easy for
researcher to use secondary data for his research.
2.Cost Effective : Collecting secondary data is cost effective. The
secondary data is available to researcher through internal or secondary
sources. The researcher does not require to appoint and trained staff to
collect data or make any conduct survey or experiments.
3.Complimentary to Primary Data : The Secondary data is
information collected and processed by other researcher for some other
issue hence it may not be hundred percent relevant for the research
problem of the researcher. In such scenario Secondary Data can be
used to support the primary data collected by the researcher.
4.Less Time Consuming : The secondary data is readily available to the
researcher trough various internal and external sources hence
collection of secondary data is quick and less time consuming for the
researcher.
5.No Sampling errors : The secondary data is readily available to the
researcher trough various internal and external sources. There is no
any requirement of sampling for collecting of secondary data hence
there os no any issue of sampling error ion Secondary Data.munotes.in
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454.2.3 Limitations of Secondary Data
1.Unsuitable : Secondary data may not be suitable for all types of
research. Secondary data is not useful in case of commercial research.
In case data is required to solve a business problem for example
customer satisfaction. In such case Secondary Data is not suitable
researcher need to collect primary data to solve this problem.
2.Accuracy : Secondary data may not be accurate. Secondary data
available to researcher may not be genuine which results in inferior
quality of secondary data. Researcher need to be careful while
selecting secondary data to be used for his research.
3.Relevance : The seco ndary data available to the researcher may not
be collected for the research which is undertaken by the researcher.
Secondary data is data collected by some other researcher earlier for
some other research problem. Considering above Secondary Data may
notbe relevant for the research.
4.Biased Information : The researcher does not have any control over
quality of secondary data. Secondary data may be affected due to bias
of researcher and respondents when it was originally collected.
5.Adequacy : The available secondary data may not be adequate for the
researcher. Secondary data is available information which was not
collected to research the problem under consideration. In such a case
researcher can not rely only on secondary data but he has to collect
primary data for his study.
4.3. METHODS / SOURCES OF COLLECTING
SECONDARY DATA
1.Internal Sources : Internal sources refers to data available within the
organisation through its own records. An organisation generates huge
data which could be useful for decision m aking. Following are varius
internal sources of Secondary Data.
a.Purchase and Sales Records
b.Record of receivables and payables
c.Record related to production
d.\Financial Statements such as Profit & Loss, Balance Sheet and
Cashflow.
e.Marketing Information
f.Record s related to employees etc.
2. External Sources : Secondary data can be collected through various
external sources also. It includes information collected from various
published sources such as books, magazines, newspapers reports,
research paper online sources etc.munotes.in
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461.Government Publications : Central, State and local government
bodies collect huge data which can be used by researchers. Following
data is collected by various government organisations.
Census which provide demographic details of population by Registrar
General of India. Statistical Information on National Income and its
various components is published by The Central Statistical
Organisation. The Director General of commercial Intelligence
provide information on Imports and Exports. Informati on on Price of
various commodities is provided by Ministry of Commerce &
Industry.
Apart from above various other bodies organisations such as Planning
Commission, Reserve Bank of India, Ministry of Finance, National
Sample Survey various boards collect an d publish information which
can be used as secondary data by the researcher.
2.Private Organisations: Apart from government there are various
private organisations which collect data and make it available to
anyone by charging some fees. In India there are o rganisations such as
The Operation Research Group, The India Market Research Bureau,
Pathfinder etc who provide required information to the researcher.
3.General Publications : It includes various publications such as
newspapers, magazines, trade and profes sional journals, research
papers, publications of various Commerce and Trade Associations. It
can also use publications made by International Organisations such as
WHO, WTO, World Bank, IMF, United Nations etc. Apart from this
researcher can also use infor mation from various specialised libraries,
reference libraries for collection of secondary data.
4.4. FACTORS AFFECTING THE CHOICE OF
METHODS OF DATA COLLECTION
The researcher needs to collect data for his research. It is a crucial
decision for the resea rcher to choose a method of data collection for his
study. The most desirable approach with regard to the selection of the
method depends on the nature of the particular problem and on the time
and resources (money and personnel) available along with the d esired
degree of accuracy needed for the study. There are several factors that
affect the decision to choose a particular method of collecting data which
are as follows.
1.Nature, scope and object of enquiry: This constitutes the most
important factor affec ting the choice of a particular method. The
method selected should be such that it suits the type of enquiry that is
to be conducted by the researcher. This factor is also important in
deciding whether the data already available (secondary data) are tomunotes.in
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47beused or the data not yet available (primary data) are to be
collected.
2.Availability of funds: Availability of funds for the research project
determines to a large extent the method to be used for the collection
of data. When funds at the disposal of the re searcher are very limited,
he will have to select a comparatively cheaper method which may
not be as efficient and effective as some other costly method.
Finance, in fact, is a big constraint in practice and the researcher has
to act within this limitation .
3.Time factor: Availability of time has also to be taken into account in
deciding a particular method of data collection. Some methods take
relatively more time, whereas with others the data can be collected in
a comparatively shorter duration. The time at the disposal of the
researcher, thus, affects the selection of the method by which the
data are to be collected.
4.Precision required: Precision required is yet another important
factor to be considered at the time of selecting the method of
collection of d ata.
5.Availability of Research Staff : This is also an important factor
while selecting a method to collect primary data researcher may have
to appoint trained staff who can collect and process data. Without
trained staff it is highly difficult for the rese archer to collect and
process data hence it is an important factor in selecting data
collection method.
6.Availability of Respondent : Availability of respondents is also a
crucial factor while deciding data collection method. No of
respondents from which da ta can be collected in a given time frame
decide the method of collecting data. If no of respondents are less,
Researcher can prefer personal interview, if the number is large then
he may prefer mail survey.
4.5 QUESTIONNAIRE
4.5.1. Meaning
Questionnaire is an important tool for collecting primary data. It
wasfirst developed by the Statistical Society of London in 1838 and has
been in continuous use ever since. A Questionnaire is a list of questions
that researchers ask to the respondents for collection of information
related to the research problem. There are different types of
questionnaire which are listed below.
1.Formal standardized questionnaire : Standardized questionnaire is
also known as struc tured questionnaire. This type of questionnaire is
scientifically designed and segmented to collect accurate information
from the respondents. This questionnaire is used to collect quantitative
data which is information recorded as a count or numerical val ue.munotes.in
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48Standardized questionnaires are best used when researcher have
already formed an initial hypothesis. These questionnaires can be
further classified into
a.Close Form Questionnaire : This tye of questionnaire do not give
too many choices to the respondent s, rather respondent have to
select answer from given options only. For example options
provide could be Yes / No True / False Agree / Disagree
b.Open Ended Questionnaire : In this type of questionnaire
respondent is not provided with options to select as an swer rather
respondent can answer the questions in descriptive manner.
2.Exploratory questionnaire : Exploratory Questionnaire is also known
as unstructured questionnaires. They’re used to collect qualitative data
which is information that can be observ ed and recorded but isn’t
numerical in nature. In this type of questionnaire there is no any specific
segmentation of questions for collection of information.Exploratory
questionnaires are ideal for conducting interviews. The researcher or
Interviewer with the help of an unstructured questionnaire can obtain
information far better than a structured questionnaire, reason for this is an
unstructured questionnaire gives flexibility to the interviewer while
conducting the interview. It is best suitable when a r esearcher is in the
early stages and want to learn more about a topic before designing a
solution or hypothesis.
3. Scaled questionnaires: In this type of questionnaire the researcher
designed the questionnaire in a such way that the while answering the
questions respondents are asked to scale the answers based on a given
rating prescribed by the question.
4. Pictorial Questionnaire : This type of questionnaire is not regularly
used. In this type of questionnaire researcher provide various pictures /
images and ask respondents to choose from the given set of images as
their response to the given question.
5. Codified and Uncodified Questionnaire : In case of codified
questionnaire researcher assign codes to the expected answers and
respondents ar e expected to fill in the code while answering the questions.
An uncodified questionnaire is a simple plain questionnaire without using
any codes
4.5.2. STEPS IN DESIGNING QUESTIONNAIRE
Designing a proper questionnaire is a key for success in research.
Researcher need to be careful while designing the questionnaire which
will be used for collecting data for his research. Followings are steps
involved in the development of a questionnaire:
1. Decide the information required.
2. Define the target respondent s.
3. Choose the method(s) of reaching your target respondents.munotes.in
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494. Decide on question content.
5. Develop the question wording.
6. Put questions into a meaningful order and format.
7. Check the length of the questionnaire.
8. Pre test the questionnaire.
9.Develop the final survey form.
1.Deciding on the information required : While designing the
questionnaire researcher needs to understand his research problem.
Through understanding of the research problem in deciding what
information is required to be coll ected for the research. This
understanding helps the researcher in drafting relevant questions.
2.Define the target respondents : The researcher needs to know from
whom the information needs to be collected for his research. The
questionnaire needs to be fra med taking into consideration respondents
familiarity of the language, status, technical words, age, education etc
of the respondents.
3.Choose the method(s) of reaching target respondents : Considering
the information needed and respondents from whom the in formation is
collected. The researcher needs to decide on a method of collecting
information. There are different methods of collecting data such as
Personal Interview, group interview, mailed questionnaire etc. The
method of collecting data plays an impor tant role in designing
questionnaire.
4.Decide on question content : The researcher should carefully decide
on contents of questionnaire. He need to be vigilant on contribution of
question towards achievement of research objectives and its use in
hypothesis testing. The researcher should avoid all irrelevant questions
the he may be tempted to include in the questionnaire. The researcher
also need to decide on type of questions to be used for collecting
information for eg. Open Ended Questions, Closed Ended Q uestions,
Pictorial Questions etc.
5.Develop the question wording : After deciding questions to be used
in questionnaire the researcher need to focus on framing the questions
using appropriate language. The researcher need to be careful while
framing the que stions, he must ensure simple and easy to understand
words are used in the questionnaire. He should draft question carefully
to avoid any ambiguity, confusion and care also need to be taken that
question does not offend respondents.
6.Put questions into a meaningful order and format : The next
step in designing a questionnaire is to decide the logical
sequence of the questions to be included in the questionnaire.
Deciding a sequence of questions is important as it helps in
collecting accurate information an d avoiding confusion of the
respondents while answering the questions.munotes.in
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507.Check the length of the questionnaire : Once the logical
sequence is decided the researcher needs to check the length of
questionnaire. It means he needs to check no of questions asked
in the questionnaire. A good questionnaire tries to obtain
maximum information in minimum possible questions. If
required, researchers will edit the questions if required and
finalise the draft of the questionnaire.
8.Pretest the questionnaire : The researc her must undertake a
pilot study before starting collecting data for the study. He
should evaluate problems faced by the interviewer and
respondents while answering the questions asked in the
questionnaire. He also needs to look into information collected
from the questionnaire. This step is really important as it checks
the usefulness of the questionnaire in the research.
9.Develop the final survey form : After conducting a pilot survey
the researcher may edit the questionnaire. This is necessary to
obtain r eliable and accurate data which decides success of the
research work. Once final editing is done the researcher prepares
the final draft of the questionnaire which will be used for
collecting data for the research work.
4.5.3. ESSENTIALS OF GOOD QUESTIONN AIRE
To draft a questionnaire or schedule is an art. The success of
statistical investigation depends on proper drafting of the questionnaire. It
is a highly specialized job and following points should be borne in mind:
1. Brief and Limited Questionnaire: The number of questions in a
questionnaire should be brief and limited as possible. Only relevant
questions to the problem under investigation should be included in the
questionnaire. This is important because respondent may run out of
patience while answe ring lengthy questionnaire and may not answer all
questions.
2. Simple and Clear: The questions asked in the questionnaire should be
simple, clear and precise. Its language used for the questions should be
easy so that informants may easily understand and respond to the question.
If respondent does not understand the question he may skip the question or
may provide irrelevant and wrong information
3. Unambiguous Questions : The questionnaire should not contain any
ambiguous question. If any question creates ambiguity for the respondents
it will irritate him and again he may provide wrong or irrelevant
information while answering such question
4. No Personal Questions: The researcher while designing questionnaire
should refrain from asking personal questions to the respondents. The
respondents may avoid answering such questions.munotes.in
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515. Avoidance of Calculations: Questions should not be based on
calculations. Only those questions should be asked which the respondents
may reply immediately. Moreover, questions shou ld avoid memories.
6. Sequence of the Questions: The questions in a questionnaire should
have a logical sequence A questionnaire with logically arranged questions
encourage respondents to provide accurate information to the researcher.
7. Pre testing: Theresearcher must conduct a pilot study before sending
the questionnaire to the respondents. Such pretesting is needed to ensure
questionnaire is properly designed and useful in collecting required
information.
8. Instructions: The questionnaire must provid e instruction to the
respondents in respect of How to fill the questionnaire. Such instructions
should be given as a footnote in the questionnaire.
9. Cross Examination: The questionnaire should be set in such a way that
there may be cross examination of t he information supplied by the
informants. In fact, it is a check on false or inaccurate answers.
10. Attractive Questionnaire: Apart from the quality of questions in the
questionnaire the researcher needs to take care of the physical appearance
of the que stionnaire. A questionnaire with good physical appearance
encourage respondent to answer the questions truthfully.
4.6. SUMMARY
This unit had given in depth information on Secondary Data. It
also discusses various factors which affect the decision of ch oosing a
method of data collection. It provide detailed information in respect of
questionnaire, its types, questions asked in questionnaire etc. Both units of
Research process collective provide basic information to learner regarding
Research Process, Da ta collection, various methods of data collection, its
advantages and disadvantages etc
4.7. EXERCISE
1.Explain sources of Secondary Data
2.What are factors influencing choosing method of data collection
3.Explain steps in designing questionnaire
4.Explain diffe rent types of questionnaire
5.Explain essentials of good questionnaire
State following statements are True or False
1.Questionnaire is used to collect Secondary Data
2.Generally lengthy questionnaires are advisable for collecting data.
3.Tabulation of data helps in analysis and interpretation of datamunotes.in
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524.Internal sources of secondary data collection include Government
Statistics.
5.Collection of Secondary Data is time consuming than primary data
( True 3F a l s e 1,2,4,5)
4.8 REFERENCE
Research Methodology : Michale Vaz, Aurora Vaz : Manan Prakashan
Research Methodology Methods and Techniques : C. R. Kothari, New
Age International Publishers
Research Methodology : R Panneerselvam, PHL Learning
munotes.in
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53Module III
DATA PROCESSING AND STATISTICAL ANALYSIS
5
DATA PROCESSING
Unit Structure
5.0Objectives
5.1. Introduction
5.2. Methods of Data Processing in Research
5.3. Statistical Analysis
5.4. Measures of Dispersion
5.5. Summery
5.6. Exercise
5.7. Reference
5.0. OBJECTIVES :
1. To know the concept of data processing
2. To explain the different statistical methods in research analysis
3. To understand the concept of hypothesis testing and various statistical
test
4. To understand the significance and precautions in data analysis
5.1. INTRODUCTION
Quantitative information may be found almost everywhere. But not
all numerical data is statistical so it is necessary to examine a few
definitions of statistics an d to understand the features of statistical data.
One of the most important objectives of statistical analysis is to get one
single value that describes the characteristics of the entire mass of
unwieldy data. Such a value is called central value.
5.2.METHODS OF DATA PROCESSING IN RESEARCH
5.2.1. Data Processing :
Data processing is a set of methods that are used to input, retrieve,
verify, store, organize, analyse or interpret a set of data. Data processing
enables information to be automatically ext racted from data. Data
processing starts with data in its raw form and converts it into a more
readable format (graphs, documents, etc.), giving it the form and contextmunotes.in
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54necessary to be interpreted by computers and utilized by employees
throughout an organi zation.
The essence of data processing in research is data reduction. Data
reduction involves sorting out the irrelevant from the relevant data and
establishing order from chaos and giving shape to a mass of data.
Data processing in research consists of five important steps. They are
following :
5.2.2. Editing of Data :
Editing is the first step in data processing . Editing is the process
of examining the data collected in questionnaires/schedules to detect
errors and omissions and to see that they are co rrected and the schedules
are ready for tabulation. When the whole data collection is over a final and
a systematic check up is made.
Mildred B. Parten in his book points out that the editor is
responsible for seeing that the data are;
i.Accurate as possib le
ii.Consistent with other facts secured
iii.Uniformly entered
iv.As complete as possible
v.Acceptable for tabulation and arranged to facilitate coding
tabulation.
5.2.3. Different types of editing .
i.Editing for quality asks the following questions:
Are the data fo rms complete?
Are the data free of bias?
Are the recordings free of errors?
Are the inconsistencies in responses within limits?
Are there evidences to show dishonesty of enumerators or
interviewers?
Are there any excessive manipulation of data? Etc.
i.Editi ng for tabulation does certain accepted modification to data
or even rejecting certain pieces of data in order to facilitate
tabulation. Orfor instance, extremely high or low value data item
may be ignored or bracketed with suitable class interval.
ii.Field E diting is done by the respondent. The schedule filled up by
the respondent might have some abbreviated writings, illegible
writings etc. These are rectified by the enumerator. This should be
done soon after the enumeration or interview.munotes.in
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55iii.Central Editing isdone by the researcher after getting all
schedules or questionnaires or forms from the respondents.
Obvious errors can be corrected. For missed data or information,
the editor may substitute data or information by reviewing
information provided by likely placed other respondents. A
definite inappropriate answer is removed and “no answer” is
entered when reasonable attempts to get the appropriate answer fail
to produce results.
5.2.4. Coding of Data :
Meaning
Coding is necessary for efficient analysis and through it the several
replies may be reduced to a small number of classes which contain the
critical information required for analysis.
Coding decisions should usually be taken at the designing stage of
the questionnaire. This makes it possible to pre code the questionnaire
choices and which in turn is helpful for computer tabulation as one can
straight forward key punch from the original questionnaires. But in case of
hand coding some standard method may be used. One such standard
method is to code in t he margin with a colored pencil. The other method
can be to transcribe the data from the questionnaire to a coding sheet.
Whatever method is adopted, one should see that coding errors are
altogether eliminated or reduced to the minimum level.
Coding is th e process/operation by which data/responses are
organized into classes/categories and numerals or other symbols are given
to each item according to the class in which it falls. In other words, coding
involves two important operations;
i.deciding the categor ies to be used and
ii.allocating individual answers to them.
These categories should be appropriate to the research problem,
exhaustive of the data, mutually exclusive and unidirectional. Since the
coding eliminates much of information in the raw data, it is important that
researchers design category sets carefully in order to utilize the available
data more fully.
In the case of pressing –coded questions, coding begins at the
preparation of interview schedules. Secondly, coding frame is developed
by list ing the possible answers to each question and assigning code
numbers or symbols to each of them which are the indicators used for
coding. The coding frame is an outline of what is coded and how it is to be
coded. That is, coding frame is a set of explicit rules and conventions that
are used to base classification of observations variable into values which
are which are transformed into numbers.
After preparing the sample frame the gradual process of fitting the
answers to the questions must be begun. Last ly, transcription is undertakenmunotes.in
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56i.e., transferring of the information from the schedules to a separate sheet
called transcription sheet. Transcription sheet is a large summary sheet
which contain the answer/codes of all the respondents. Transcription may
not be necessary when only simple tables are required and the number of
respondents are few.
5.2.5. Classification of Data :
Classification or categorization of data is the process of grouping
the statistical data under various understandable homogeneous groups for
the purpose of convenient interpretation. A uniformity of attributes is the
basic criterion for classification and the grouping of data is made
according to similarity. Classification becomes necessary when there is
diversity in the data collect ed for meaningless presentation and analysis.
However, it is meaningless in respect of homogeneous data. A good
classification should have the characteristics of clarity, homogeneity,
equality of scale, purposefulness and accuracy.
5.2.6. Objectives of Cl assification of data are below:
i.The complex and scattered data is organized into logical and
intelligible form.
ii.It is possible to make the characteristics of similarities and dis –
similarities clear.
iii.Comparative studies is possible.
iv.Understanding of the s ignificance is made easier and thereby good
deal of human energy is saved.
v.Underlying unity amongst different items is made clear and
expressed.
vi.Data is so arranged that analysis and generalization becomes
possible.
5.2.7. Types of Classification of data :
Classification of data is of two types
ii.Quantitative classification : It is on the basis of variables or quantity
iii.Qualitative classification : It is classification according to attributes.
The quantitative classification is the way of grouping the vari ables,
say, quantifying the variables in cohesive groups, while the qualitative
groups the data on the basis of attributes or qualities.
Again, it may be multiple classification or dichotomous
classification. The former is the way of making many (more th an two)
groups on the basis of some quality or attributes while the latter is the
classification into two groups on the basis of presence or absence of a
certain quality. Grouping the workers of a factory under various income
(class intervals) groups come under the multiple classification and makingmunotes.in
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57two groups into skilled workers and unskilled workers is the dichotomous
classification. The tabular form of such classification is known as
statistical series, which may be inclusive or exclusive.
5.2.8. Tabul ation of Data :
Tabulation is the process of summarizing raw data and displaying
it in compact form for further analysis. Therefore, preparing tables is a
very important step. Tabulation may be by hand, mechanical, or
electronic. The choice is made largely on the basis of the size and type of
study, alternative costs, time pressures, and the availability of computers,
and computer programmes. If the number of questionnaire is small, and
their length short, hand tabulation is quite satisfactory.
Table may b e divided into: (i) Frequency tables (ii) Response tables (iii)
Contingency tables (iv) Uni variate tables (v) Bi variate tables (vi)
Statistical table and (vii) Time series tables.
Necessary steps in the preparation of table :
i.Title of table: The table sh ould be first given a brief, simple and
clear title which may express the basis of classification.
ii.Columns and rows: Each table should be prepared in just
adequate number of columns and rows.
iii.Captions and stubs: The columns and rows should be given
simple and clear captions and stubs.
iv.Ruling: Columns and rows should be divided by means of thin or
thick rulings.
v.Arrangement of items : Comparable figures should be arranged
side by side.
vi.Deviations: These should be arranged in the column near the
original data so that their presence may easily be noted.
vii.Size of columns: This should be according to the requirement.
viii.Special emphasis: This can be done by writing important data in
bold or special letters.
ix.Foot –notes: These may be given below the table.
x.Total: Totals of each column and grand total should be in one line.
xi.Source : Source of data must be given. For primary data, write
primary data.
It is always necessary to present facts in tabular form if they can be
presented more simply in the body of the text. Ta bular presentation
enables the reader to follow quickly than textual presentation. A table
should not merely repeat information covered in the text. The same
information should not, of course be presented in tabular form and
graphical form. Smaller and sim pler tables may be presented in the textmunotes.in
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58while the large and complex table may be placed at the end of the chapter
or report.
5.2.9. Data Diagrams :
Diagrams are charts and graphs used to present data. These
facilitate getting the attention of the reader more. These help presenting
data more effectively. Creative presentation of data is possible.
The data diagrams classified into as follows :
i.Charts: A chart is a diagrammatic form of data presentation. Bar
charts, rectangles, squares and circles can be u sed to present data. Bar
charts are uni dimensional, while rectangular, squares and circles are
twodimensional.
ii.Graphs: The method of presenting numerical data in visual form is
called graph, A graph gives relationship between two variables by
means of e ither a curve or a straight line.
Graphs may be divided into two categories.
a.Graphs of Time Series and
b.Graphs of Frequency Distribution.
5.2.10 Significance of Data Processing in Research:
Data processing helps to make reports easy because the data has
been processed, it can be used directly. These processed data can
be organized in such a way that they can help to conduct analysis
quickly. Predefined data helps experts in making conclusions
faster.
Data processing maintains accuracy and speed in da ta analysis.
Complex data can be processed in a minute and can store
necessary data. In the processing of research data, the system will
automatically check and process invalid data. Therefore, such
processes help researchers to ensure high accuracy in da ta
management.
Data processing is very helpful in breaking a macro problem into a
micro problem. It helps to detect errors and omissions.
Data processing acts like a filter when it comes to acquiring
meaningful insights out of a huge data set.
Data processing helps in keeping human bias away from the
research conclusion with the help of proper statistical treatment.
Data processing further helps in cost reduction, ease in storage,
distributing and report making followed by better analysis and
presentation are other advantages.munotes.in
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595.3. STATISTICAL ANALYSIS: TOOLS AND
TECHNIQUE
Masseurs of Central Tendency:
5.3.1. Definition:
A measure of central tendency is a representative number that
characterizes the “middleness” of an entire set of data. The th ree measures
of central tendency are the mean, the median, and the mode.
The term central tendency or average have been defined by various
researchers in following ways
Simpson and Kafka “ A measure of central tendency is a typical value
around which o ther figures congregate”
Clark “Average is an attempt to find one single figure do describe whole
of figures”
It is clear from the above definitions that an average is a single
value which represents a whole series and is supposed to contain its major
characteristics.
5.3.2. Types of Averages :
Measure of central tendency or averages are usually of the
following types :
1) Mathematical Averages :
I.Arithmetic Average or mean
II.Geometric mean
III.Harmonic mean
2) Averages of position :
II.Median
III.Mode
Of the above mentioned five important averages, Arithmetic mean,
median and mode are the most popular ones. Besides these there are other
averages like Quadratic mean, moving average and progressive average
etc. Moving and progressive averages are used in the ana lysis of
commercial statistics. Quadratic mean not so used in analysis.
5.3.3. Arithmetic Mean :
The most widely used measure of representing the entire data by one
value is generally called an average and what the statistician call is
arithmetic mean. Its value is obtained by adding together all the items and
by dividing this total by the number of items. Arithmetic means may
either be :
i.Simple arithmetic mean
ii.Weighted arithmetic meanmunotes.in
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60i.Calculation of Simple Arithmetic mean :
The process of computin g mean is case of individual series. At first
add together the various values of the variable and divide the total by
the number of items. Symbolically,
µ (pronounced “mu”) = the symbol for the population mean i.e.
Arithmetic mean ;
X1+X2+……….Xn = Val ue of variable
N = Number of observations
Short cut Method :
Arithmetic mean cab be calculated by using an arbitrary origin
when deviations are taken from an arbitrary origin. The formula for
calculating mean is
A = assumed mean
d = deviations value s form assumed mean
Calculation of mean Discrete series :
In discrete series mean
mat be computed by applying direct method
of shortcut method.
Direct Method :
The formula for computing mean is
= frequency
variables in questions
total number of items
Short Cut method :
The formula for computing mean is
Calculation of Arithmetic mean: Continuous Series
In continuous series arithmetic mean may be computed by applying any
of the following methods.
Direct Method :
m = mid value of class
f = the frequency of each classmunotes.in
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61Shortcut method :
A= Assumed mean
d = deviations of mid points from assumed mean
N = total number of observation
5.3.4. Merits and limitations of Arithmetic mean :
Merits :
i.It is the simplest average to understand and to compute
ii.It is affected by the value of every item in the series
iii.It is suitable for further mathematical treatment
iv.It is least affected by the fluc tuations of sampling
5.3.5. Limitations :
i.Sometime the abnormal items may considerably affect the average
value when the number of items is not large.
ii.In a distribution with open and classes the value of mean cannot be
computed without making assumption regarding the size of the
class interval of the open end class.
5.3.6. Median
Meaning
Another measure of central tendency, the median, is used in
situations in which the mean might not be representative of a distribution.
The median by definition refer s to the middle value in a distribution.
Yule and Kendall “the median may be defined as the middle most
or central value of the variable when the values are arranged in ascending
or descending order. In case of a frequency curve the median may be
defined as that value of the variable which divides the area of the curve
into two equal parts”
The median is the middle score in a distribution after the scores
have been arranged from highest to lowest or lowest to highest. The point
to remember is that the med ian is not affected by extreme scores in a
distribution because it is only a positional value. The mean is affected by
extreme scores because its value is determined by a calculation that has to
include the extreme values.
Median is called as a positional average. The terms ‘position’
refers to the place of a value in a series. The median is calculated by
averaging the two middle scores. In other words, we determine the middle
point between the two middle scores. Median is thus the central value of
the dist ribution or the value that divides the distribution into two parts.munotes.in
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62Calculation of Median :
The calculation of median involves two basic steps.
i.The location of the middle item an d
ii.Finding out its value
The middle item in series of individual obser vation and also in a
discrete series is
Where N is the total number of observations.
In case of continues series (N/2)thitem is the middle item of the
series.
Once the middle item is located its value has to be found out. In a
series of individual observation if the total number of items is an odd
figure, the value of the middle item is the median value. If N is even,
median is half the sum of the two middle values.
Problem :
Find out the median of the following items
7,9,15,17,22,25,29,35,40
Solution :
These items would first be arranged in ascending order of
magnitude the series then would be as follows
Sr. No Size of items
1 7
2 9
3 15
4 17
5 22
6 25
7 29
8 35
9 40
thitem
thitem
M= 5thitem
Thus M = 22
Computation of Median in a Discrete series:
The various steps in the computation of median in a discrete series
are as follows:
i.Arrange the values in ascending or descending order of magnitude
ii.Find out the cumulative frequenciesmunotes.in
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63iii.Find out the diddle i tem by the formula
thitem
iv.Now find out the value of
thitem. It can be found by
first locating the cumulative frequency which is equal to
or next higher to it and then determining the value
corresponding to it. This w ill be the value of the median.
Solution :
Find out then value of median from the following data
Marks : 4, 6,8,10,12
Students : 5,1,4,2,3
Marks in ascending
order (X)Students
(Frequency )Cumulative
frequency (C.F)
4 1 1
6 4 5
8 5 10
10 3 13
12 2 15
N = 15
Median is the value of
thitem
thitem
thitem
7.5thitem comes under in the group of 10 Cumulative frequency.
Thus the median value would be 8
Computation of Median in a Continuous series :
While computing the value of median in a continuous series the middle
item is the (N/2)thitem and not
thitem
In a continues frequency distribution the value of median would be in
class interval. To set a precise value of median we assume that the
frequency of the median class is uniformly spread over the whole class
interval. On this assumption the value of the median can be located by the
following formula.
Where
M = the value of medianmunotes.in
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64
= the lower limit of the class in which median lies
N/2 = the middle number
c.f. = the cumulative frequency of the median class
i = the magnitude of the median class interval
Problem and solution :
X Frequency c.f.
010 15 15
1020 17 32
2030 19 51
3040 27 78
4050 19 97
5060 13 110
N = 10
Median value of N/2 is 55thitem which is lies in the 30 40 class
intervals. \now applying the formula of interpolation
5.3.7. Merits of Arithmetic median :
i.It is not affected by the values of the extreme items and as s uch is
sometimes more representative than arithmetic average.
ii.Even if the value of extremes is not known median can be
calculated if the number of items is known
iii.It can be located merely by inspection in many cases.munotes.in
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655.3.8. Limitations of Arithmetic me dian:
i.For calculating median it is necessary to arrange the data other
average do not need any arrangement
ii.Since it is a positional average, its value is not determined by each
and every observations
iii.The value of median is affected more by sampling fluctu ations
than the value if arithmetic mean
5.3.9. Mode.
The third measure of central tendency is the mode —the score in a
distribution that occurs with the greatest frequency. The mode is the only
indicator of central tendency that can be used with nominal data. Although
it can also be used with ordinal, interval, or ratio data, the mean and
median are more reliable indicators of the central tendency of a
distribution, and the mode is seldom used.
The mode refers to that value in a distribution which occur s most
frequently. It is an actual value which has the highest concentration of
items in and around it. The value of the variable at which the curve
reaches a maximum is called the mode.
Calculation of Mode :
i.Individual Observations :
For ungrouped data or series of individual observations mode is
often found by mere inspection.
Example : 30,31,33,34,33,34,37,33,35,38,
Since 33 number appeared three times
Thus Mode = 33
ii.Discrete series :
In discrete series very often mode can be located merely by ins pection
as the value having the highest frequency would generally be the modal
value.
Example :
Value 7 9 10 12 15
Frequency 3 15 12 9 10
Clearly the value of mode is 9 as it carries the maximum frequency
of 15. However on all cases the maximum freq uency may not necessarily
signifies maximum frequency density.
Calculation of mode: Continuous Series
i.By preparing grouping table and analysis table or by inspection
ascertain the modal classmunotes.in
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66ii.Determine the value of mode by applying formula
Where
= lower limit of modal class
= frequency of the modal class
= frequency of the modal class preceding the modal class
= frequency of the modal class succeeding the modal class
= Size of the class interval of modal class
Example:
X 2030 3040 4050 5060 6070 7080 8090
F 8 20 25 22 10 8 7
The modal class is 40 50 since it have highest frequency i.e. 25
= 40 ,
= 25 ,
= 20 ,
=22,
= 10
Mode (
= 46.25
5.4 MEASURES OF DISPERSION
5.4.1. Meaning and Definition
As we know that the various measures of central value gives us
one single figure that represents the entire data. But the averages alone
cannot adequately describes a set of observations unless all the
observations are the same. It is necessary to describe the dispersion of the
observations. Thus measures of dispersion help us in studying important
feature of a distribution.
Brooks and Dick “Dispersion or spread is the degree of the scatter
variation of the variables about a central value.”
A measure of central tendency provides information about the
“middleness” of a distribution of scores but not about the width or spread
of the distribution . To assess the width of a distribution, we need a
measure of variation or dispersion. A measure of variation indicates the
degree to which scores are either clustered or spread out in a distribution.
As an illustration, consider the two very small distri butions of exam scores
shown in following table.munotes.in
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67Class 1 Class 2
0 45
50 50
100 55
= 150
=150
Notice that the mean is the same for both distributions. If these
data represented two very small classes of students, r eporting that the two
classes had the same mean on the exam might lead you to conclude that
the classes performed essentially the same. Notice, however, how different
the distributions are. Providing a measure of variation along with a
measure of central t endency conveys the information that even though the
distributions have the same mean, their spreads are very different.
We will discuss three measures of variation: the range, the mean
deviation, and the standard deviation. The range can be used with or dinal,
interval, or ratio data however, the standard deviation and average
deviation are appropriate for only interval and ratio data.
A.Range :
The simplest measure of variation is the range —the difference
between the lowest and the highest scores in a d istribution. The range is
usually reported with the mean of the distribution. To find the range, we
simply subtract the lowest score from the highest score. In our
hypothetical distributions of exam scores in above table, the range for
Class 1 is 100 point s, whereas the range for Class 2 is 10 points. Thus, the
range provides some information concerning the difference in the spreads
of the distributions. In this simple measure of variation, however, only the
highest and lowest scores enter the calculation, and all other scores are
ignored. Thus, the range is easily distorted by one unusually high or low
score in a distribution.
B.Mean Deviation:
It is the more sophisticated measures of variation use all of the scores
in the distribution in their calculation . The average which is frequently
used in computing the mean deviation is mean or median.
Mean deviation denoted by Greek letter, small “ δ”. The sign of
average taken in deviation s used as subscript.
δxor= mean deviation form mean
δM= mean deviati on from median
δM0= Mean deviation from mode
Coefficient of mean Deviation :
Mean deviation when is divided by the average used for
calculating it we get coefficient of mean deviation.munotes.in
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68
Computation of Mean Deviation : Individual series
There are tw o methods of calculating the mean deviation from a
series of individual observations.
i.Direct Method :
The word deviation means to diverge, move away from, or digress. In
this method the mean deviation would be calculated by totaling the
deviations and dividing the total by the number of items.
Mean Deviation
In the short cut method mean or median is calculated and the total
of the values of the items below the mean or median and above it are
found out. The former is subtracted from the latter and is divided by the
number of items. The resulting figure is the mean deviation.
Computation of Mean Deviation : Discrete series
In discrete series the calculation of mean deviation involve the
following steps:
i.Calculating the median or mean of the series (M)
ii.Find the deviations from the median or mean ignoring plus minus
signs
iii.Multiply the deviations with the respective frequency and get the
total
iv.Divide the total by the number of observations. This will be the
value of mean deviation.
Symbolically :
δm
and
δx
C.Standard Deviation :
The most commonly used measure of variation is the standard
deviation. In other words that might be substituted for the word standard
include average, norma l, and usual. The standard deviation means the
average movement away from something. It is the average movement
away from the center of the distribution —the mean. The standard
deviation, then, is the average distance of all the scores in the distribution
from the mean or central point of the distribution —or, the square root of
the average squared deviation from the mean.
Standard deviation first suggested by Karl Person in 1893. It may
be defined as “Root Mean Square Deviation” from the mean. It is usual ly
denoted by the Greek letter
(sigma).munotes.in
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69Calculation of standard deviation : individual observations
In case of individual observations standard deviation may be
computed by applying any of the following two methods.
i.Deviation taken fr om the actual mean :
By Taking deviation of the items from the actual mean. In the
method following formula is applied.
Steps :
i.Calculating the actual mean of the series
ii.Tae the deviations of the items from the mean
iii.Square these deviations and obtai n that total
iv.Divide
by the total number of observations i.e. N and extract
square root. This gives us the value of S.D.
ii.Deviations taken from Assumed Mean :
When deviation are taken from assumed mean the following
formula is a pplied.
Steps :
i.Take the deviations of the items from an assumed mean. Denote
these deviations by d. take the total of these deviations i.e.
obtain
ii.Square these deviations and obtain the total
iii.Substitute the values of
and N in the above formula.
Calculation of S.D : Discrete Series
i.Assumed mean method
When this method is used the following formula is applied
Where d = (X A)
Steps :
i.Take the deviations of the items from an assumed mean and denote
these dev iations by d
ii.Multiply these deviations by the respective frequencies and obtain the
total
munotes.in
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70iii.Multiply the squared deviations by the respective frequencies and
obtain the total
Substitute the value sin the above formula.
Example :
X F d= (X A) fd
10 8 30 240 900 7200
20 12 20 240 400 4800
30 20 10 200 100 2000
40 10 0 0 0 0
50 7 10 70 100 700
60 3 20 60 400 1200
N=60
ii.Step Deviation method :
When this method is used we take a co mmon factor from the given
data. The formula for computing standard deviation is:
Where
and C= common factor
Calculation of standard deviation: Continuous series
In continues series any of the method discussed above for discrete
frequenc y distribution can be used. However in practice it is the step
deviation method that is mostly used.munotes.in
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71
X F M.V
F×d
010 18 5 40 720 28800
1020 16 15 30 480 14400
72030 15 25 20 300 6000
3040 12 35 10 120 1200
4050 10 45 0 0 0
5060 05 55 10 50 500
6070 02 65 20 40 800
7080 1 75 30 30 900
N = 79
×10
×10
×10
×10
×10
5.5. SUMMARY :
The central tendency of a distribution is t ypically contrasted with
itsdispersion orvariability ; dispersion and central tendency are the often
characterized properties of distributions. Analysis may judge whether data
has a stron g or a weak central tendency based on its dispersion. In
statistics, a central tendency is a central or typical value for a probability
distribution. It may also be called a center or location of the distribution.munotes.in
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72Colloquially, measures of central tendency are often called averages. A
measure of central tendency is a summary statistic that represents the
center point or typical value of a dataset. These measures indicate where
most values in a distribution fall and are also referred to as the central
locati on of a distribution. You can think of it as the tendency of data to
cluster around a middle value.
5.6. EXERCISE:
A. Test your knowledge by choosing the correct option:
Q1. ………………. is a set of methods that are used to input, retrieve,
verify, store, o rganize, analyse or interpret a set of data. (Data processing
, Central Tendency, Parametric test, Non Parametric Statistical Tests)
Q2. ………….. involves sorting out the irrelevant from the relevant data .
( Data reduction, Data Processing, Data Collection , Data mining)
Q3……………. is done by the respondent. (Field Editing, Central
Editing, Editing for tabulation, Editing for quality)
Q4.…………….. of data is the process of grouping the statistical data
under various understandable homogeneous groups for the purpose of
convenient interpretation. (Coding, Editing, Tabulation, Classification)
Q5. The method of presenting numerical data in visual form is
called………. ( Editing,Graph, Chart, Coding)
Q6. A measure of …………tendency is a representative number that
characterizes the “middleness” of an entire set of data. (Central, Positive,
Negative, Rational)
Q7. ……….averages is not used in the analysis of commercial statistics.
(Moving, progressive, Quadratic mean, Arithmetic mean)
Q8. Which is the formula of Arithmet ic mean
i.
ii.
iii.
iv. M D
Q9. The ………….is the middle score in a distribution after the scores
have been arranged from highest to lowest or lowest to highest. ( Median,
mean, mode, co rrelation)
Q10. The ……….. refers to that value in a distribution which occurs most
frequently. ( Median, mean, mode, correlation)
Q11. The …………… is the average distance of all the scores in the
distribution from the mean or central point of the distributio n (mean,
mode, correlation, standard deviation)munotes.in
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73Q12. ………….is usually denoted by the Greek letter
(sigma) (mean,
mode, correlation, standard deviation)
(Answers –1.Data processing, 2. Data processing, 3.Field Editing,
4.Classification, 5 . Graph, 6. Central, 7. Quadratic mean,
8.
9. Median, 10. Mode, 11. standard deviation,
12. standard deviation )
B. Short Answer Questions :
1.Define data processing
2.Explain the concept editing of data
3.What is coding of data?
4.Explain Tabul ation of data.
5.Define Arithmetic mean
6.Merits and limitations of Arithmetic mean.
7.Merits and limitations of Arithmetic median.
8.What is mode?
9.Define the central tendency.
10.Explain the concept Range.
5.7 REFERENCE
I.Sherri L. Jackson, (2009) , Research Meth ods and Statistics, A
Critical Thinking Approach, ISBN 13: 978 049551001 7
II.BASIC ECONOMETRICS,(2003) Damodar N. Gujarati, McGraw 
Hill Higher Education ISBN: 978 007233542 2
III.Sachdeva J.K.(2011). Business Research Methodology. New
Delhi: Himalaya Publi shing House.
IV.Michael V.P.(1997). Research Methodology in Management.
Delhi: Himalaya Publishing House
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746
STATISTICAL ANALYSIS
Unit Structure
6.0 Objective
6.1. Introduction
6.2. Correlation Analysis
6.3. Regression Analysis
6.4. Hyp othesis Testing
6.5. Parametric and Non Parametric Statistical Tests
6.6. Factor Analysis:
6.7. Interpretation of Data
6.8. Summery
6.9. Exercise
6.10. Reference
6.0OBJECTIVE:
After studying this unit learner will be in position;
To examine the conce pt of correlation
To analyse the regression work
To understand the concept of statistical inferences
To examine the Parametric and Non Parametric Statistical Tests
To elaborate the Factor Analysis.
6.1. INTRODUCTION
In the Information Age, d ata is no longer scarce –it’s
uncontrollable. The key is to examine through the vast volume of data
available and businesses and correctly interpret its implications. But to
sort through all this information, we need the right statistical data analysis
tools. With the current obsession over big data, analysts have produced a
lot of tools and techniques for data interpretation. Statistics is a crucial
process behind how we make decisions based on data and make
predictions. Statistics tools allow researchers to understand a subject much
more deeply.munotes.in
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756.2. CORRELATION
6.2.1. Meaning:
Correlation is a statistic that measures the degree to which two
variables move in relation to each other. Corre lation shows the strength of
a relationship between two variables and is expressed numerically by the
correlation coefficient. The correlation coefficient's values range between
1.0 and 1.0. A perfect positive correlation means that the correlation
coeffi cient is exactly 1. A perfect negative correlation means that two
variables move in opposite directions, while a zero correlation implies no
linear relationship at all.
A correlation coefficient quite close to 0, but either positive or
negative, implies l ittle or no relationship between the two variables. A
correlation coefficient close to plus 1 means a positive relationship
between the two variables, with increases in one of the variables being
associated with increases in the other variable.
A correlat ion coefficient close to 1 indicates a negative
relationship between two variables, with an increase in one of the
variables being associated with a decrease in the other variable. A
correlation coefficient can be produced for ordinal, interval or ratio l evel
variables, but has little meaning for variables which are measured on a
scale which is no more than nominal.
The formula for correlation:
6.2.2. Types of correlation:
i.Positive correlation :
Positive correlation refers to the movement of the vari able in the
same direction or a direct relationship exists between the two variables.
This means that an increase in one variable is related to an increase in the
other, and a decrease in one is related to a decrease in the other. This type
of correlation exist between supply and price of commodity.
ii.Negative correlation :
Negative or inverse correlation refers to when one variable increases
or decreases the other moves in the reverse direction. Such a correlation is
found between price and demand, when p rice of a commodity increases its
demand goes down or vice versa.munotes.in
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76iii.Simple and multiple correlation :
Under simple correlation the relationship is confined to two variables
like between the yield of wheat and the use of chemical fertilizers of
between mon ey supply and the general price level.
In case of multiple correlation the relationship between more than two
variables is judged. For example the relationship of yield of wheat by
judged with reference to say chemical fertilizers irrigation and pesticid es.
iv.Partial and total correlation :
These are the two types of a multiple correlation analysis. Under
partial correlation the relationship of two or more variable is examined
excluding some other variables which are included for calculation of total
correlation. \for example coefficient of correlation between yield of wheat
and chemical fertilizers excluding the effect of pesticides and manures is
called the partial correlation. And the total correlation is based on all the
relevant variables.
v.Linear a nd non linear correlation :
The distinction between linear and non linear correlation is based
upon the ratio of change between the variables under study. When
variations in the values of two variables have constant ratio there will be
linear correlation between them. The graph of variables having such a
relationship will form a straight line. In non linear or curve liner
correlation the amount of change in the other related variable. For example
when we double the use of fertilizers the production of jut e would not
necessarily be doubled.
6.2.3. Graphic methods of determining correlation:
The different methods of finding out correlations are following.
i.Scatter Diagram :
This method is a simple and attractive method of diagrammatic
representation of a bivariate distribution for ascertaining the nature of
correlation between the variables. Pairs of values (X 1,Y 1)( X 2,Y2)
…….….(X n,Yn) or two variables X and Y can be plotted as dots (.) on the
Xaxis and Y axis in the XY plane. It is customary to tak e the
independent variable along the horizontal or X axis and the dependent
vertical along the vertical or Y axis, if at all there is called a scatter
diagram.
If the patterns of points or dots on a scatter diagrams revels an
upward or a downward trend t he variables are said to be correlated and if
the plotted points do not show any trend the two variables have no
correlation.
The scatter diagrams may take the following shapesmunotes.in
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771) Positive Correlation relationship :
It means that an increase in one variable is related to an increase in
the other, and a decrease in one is related to a decrease in the other. The
majority of the data points fall along an upward angle (from the lower left
corner to the upper right corner).
2)Negative Correlation Rela tionship :
In this scatter plot, the data points extend from the upper left to the
lower right. This negative correlation indicates that an increase in one
variable is accompanied by a decrease in the other variable. This
represents an inverse relationship : The more of variable x that we have,
the less we have of variable y. Assume that this scatter plots represents the
relationship between age and eyesight. As age increases, the ability to see
clearly tends to decrease —a negative relationship.
3) No cor relation Relationship :
It is also possible to observe no meaningful relationship between two
variables. In this scatter plot, the data points are scattered in a random
fashion. As you would expect, the correlation coefficient for these data is
very close to 0 to (.09).
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784) Curvilinear Relationship :
A correlation coefficient of 0 indicates no meaningful relationship
between two variables. However, it is also possible for a correlation
coefficient of 0 to indicate a curvilinear relationship.
Imagine t hat above graph represents the relationship between
psychological excitement (the x axis) and performance (the y axis).
Individuals perform better when they are moderately stimulated than when
stimulation is either very low or very high. The correlation co efficient for
these data is also very close to 0 (.05). The strong positive relationship
depicted in the left half of the graph essentially cancels out the strong
negative relationship in the right half of the graph. Although the
correlation coefficient is very low, we would not conclude that no
relationship exists between the two variables.
As the graph shows, the variables are very strongly related to each
other in a curvilinear manner —the points are tightly clustered in an
inverted U shape. Correlati on coefficients tell us about only linear
relationships. Thus, even though there is a strong relationship between the
two variables graph, the correlation coefficient does not indicate this
because the relationship is curvilinear. For this reason, it i si mportant to
examine a scatter plot of the data in addition to calculating a correlation
coefficient. Alternative statistics can be used to assess the degree of
curvilinear relationship between two variables.
6.3. REGRESSION ANALYSIS
Regression lines are the device used for estimating the value of one
variable from the value of the other consists of a line through the points
drawn in such a manner as to represent the average relationship between
the two variables. Such a line is called the line of regressi on.
As per the method of least square the two regressions lines are
The general form of each type of regression is:
Simple linear regression: Y=a+b X+u
Multiple linear regression: Y=a+b 1X1+b2X2+b 3X3+ ... + b tXt+umunotes.in
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79Where:
Y = the variab le that you are trying to predict (dependent variable).
X = the variable that you are using to predict Y (independent
variable).
a = the intercept.
b = the slope.
u = the regression residual
Multiple regression analysis is used to see if there is a statistically
significant relationship between sets of variables . It’s used to find trends in
those sets of data .
Multiple regression analysis is almost the same as simple linear
regression . The only difference between sim ple linear regression and
multiple regression is in the number of predictors (“x” variables) used in
the regression.
Simple regression analysis uses a single x variable for ea ch
dependent “y” variable. For example: (x1, Y1).
Multiple regression uses multiple “x” variables for each
independent variable : (x1)1, (x2)1, (x3)1, Y1).
In one variable lin ear regression, you would input one dependent
variable (i.e. “sales”) against an independent variable (i.e. “profit”). But
you might be interested in how different types of sales effect the
regression. You could set your X1 as one type of sales, your X2 as another
type of sales and so on.
6.3.1. Two lines of regression:
Since the regression relation is irreversible one equation is not
sufficient to predict the values of two vari ables X and Y. moreover the two
regression equations are derived under different set of assumptions,
therefore one equation is not sufficient to find X and Y.
6.3.2. Properties of Regression coefficients :
i.Both the regression coefficients should be of th e same sign.
ii.If both the regression coefficients are positive, correlation coefficient is
positive and if both the regression coefficients are negative the
correlation coefficient is negative.
iii.Both the regression coefficient are independent of the change of origin
but if the change of scale in X and Y is not identical they depend on the
change of scale. If the change of scale in X and Y is identical the
regression coefficients are independent of the change of scale also.
iv.The correlation coefficient is t he geometric mean between the
regression coefficients.munotes.in
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806.4. HYPOTHESIS TESTING
6.4.1. Meaning:
Hypothesis testing is an act in statistics where by an
analyst tests an assumption regard ing a population parameter. The
methodology employed by the analyst depends on the nature of the data
used and the reason for the analysis. Hypothesis testing is used to assess
the plausibility of a hypothesis by using sample data. Such data may come
from a larger population, or from a data generating process.
Hypothesis testing was introduced by Ronald Fisher ,Jerzy
Neyman ,Karl Pearson and Pearson’s son, Egon Pea rson.Hypothesis
testing is a statistical method that is used in making statistical decisions
using experimental data. Hypothesis Testing is basically an assumption
that we make about the population parameter .
6.4.2. Steps of Hypothesis Testing :
i.Allhypotheses are tested using a four step process:
ii.The first step is for the analyst to state the two hypotheses so that
only one can be right.
iii.The next step is to formulate an analysis plan, which outlines how
the data will be evaluated.
iv.The third step is t o carry out the plan and physically analyze the
sample data.
v.The fourth and final step is to analyze the results and either reject
the null hypothesis, or state that the null hypothesis is plausible,
given the data.
6.4.3. Null hypothesis:
Null hypothesi s is a statistical hypothesis that assumes that the
observation is due to a chance factor. A statistical hypothesis which is
under test, usually a hypothesis of no difference and hence, it’s called Null
hypothesis. Null hypothesis is denoted by : H 0:μ1=μ2, which shows that
there is no difference between the two population means.
A.R. Fisher “null hypothesis is the hypothesis which is tested for possible
rejection under the assumption that it is true.”
6.4.4. Alternative hypothesis:
Contrary to the null hypothesis, the alternative hypothesis shows
that observations are the result of a real effect. Rejecting null hypothesis
implies that it is rejected in favour of some other hypothesis which is
accepted. A hypothesis which is accepted when H 0isrejected is called
Alternative hypothesis and is represented by H 1.munotes.in
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81Usually the null hypothesis is expressed as an equality e.g. H 0
:theta θ = θ0
6.4.5. Rules of stating Null and Alternative hypothesis :
i.The conclusion expected as a result of the test should be placed in
the Alternative hypothesis
ii.The null hypothesis should contain a statement of equality either
≤,≥or =
iii.Thenull hypothesis is the hypothesis that is tested.
iv.The null and alternative hypothesis are complementary
6.4.6. Level of significance:
The level of significance is defined as the probability of rejecting
Null hypothesis when it is true. It is the maximum size of the type I error
which we are prepared to risk. It refers to the degree of significance in
which we accept or reject the null hypothesis. 100% accuracy is not
possible for accepting or rejecting a hypothesis, so we therefore select a
level of sign ificance that is usually 5%. The higher the level of
significance is, the higher the probability of rejecting a null hypothesis
when it is true. Level of significance is always fixed in advance before the
sample information.
6.4.7. Types of error :
When we test hypothesis there are four possible outcomes.
i.Null hypothesis is rejected when it is true
ii.Null hypothesis is rejected when it is false
iii.Null hypothesis accepted when it is false
iv.Null hypothesis is accepted when it is true.
Outcomes i and iii are undesirable. We may think of these two
undesirable outcomes as incorrect actions and distinguish them by
referring to them as Type I and Type II errors. The error of rejecting H 0
when H 0is true is known as type I error and error of accepting H 0when H 0
isfalse known as type II error.
If
P( r e j e c t i n gH 0when H 0is true) = P (Type I error ) = α
P (accepting H 0when H 0is false) = P (Type II error ) = β
These are also called the sizes of type I error and type II error
respectively. The sizes f type I and type II errors are also known as
producer’s risk and consum er’s risk respectively.
Type I error: When we reject the null hypothesis, although that
hypothesis was true. Type I error is denoted by alpha ( α).In hypothesis
testing, the normal curve that shows the critical region is called the alpha
region.
Type II errors: When we accept the null hypothesis but it is false. Type
II errors are denoted by beta ( β).In Hypothesis testing, the normal curve
that shows the acceptance region is called the beta region.munotes.in
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826.4.8. Power of test :
Usually known as the probability of correctly accepting the null
hypothesis. The good test should a ccept the null hypothesis when it is true
and reject the null hypothesis when it is false. 1 βis called power of the
analysis or probability of type II error. It measures how well the test is
working and is called the power of the test. A high value of 1βimplies
the test is working quite well. A low value of 1 βimpels the test is
working very poorly.
A. One tailed test:
When the given statistical hypothesis is one value like H0: μ1=μ2, it is
called the one tailed test. For example a test for te sting the man of a
population
H0:μ=μ0
Against the alternative hypothesis.
H1:μ>μ0(right tailed ) or H 1:μ<μ0(left tailed) is a single tailed test. In
the right tailed test the critical region lies entirely in the right tail of the
sampling distr ibution, while for the left tailed test the critical region is
entirely in the left tail of the distribution of mean.
B. Two tailed test:
When the given statistics hypothesis assumes a less than or greater than
value, it is called the two tailed test. A test of statistical hypothesis where
the alternative hypothesis is two tailed such as
H0:μ=μ0
Against the alternative hypothesis
H1:μ≠ μ0is known as two tailed test and in such a case the critical region
is given by the portion of the area lying in both the tails of the probability
curve of the test statistic.
6.5. PARAMETRIC AND NON PARAMETRIC
STATISTICAL TESTS :
Meaning:
Aparameter in statistics refers to an aspect of a population, as
opposed to a statistic , which refers to an aspect about a sample . For
example, the population mean is a parameter, while the sample mean is a
statistic. A parametric statistical test makes an assumption about the
population parameters and the distributions that the data came from.
The pa rametric test make certain assumptions about a data set
namely –that the data are drawn from a population with a specific or
normal distribution. It is further assumed in parametric test that the
variables in the population are measured based on an interv al scale.
Parametric tests are used when the data has a normal distribution
and when the measurement scale is interval or ratiomunotes.in
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836.5.1. Types of Parametric test :
Twosample t test
Paired t test
Analysis of variance (ANOVA)
Pearson coefficient of correla tion
I.tTest :
Attest is a type of inferential statistic used to determine if there is
a significant difference between the means of two groups, which may be
related in certain features. It is mostly used when the data sets, like the
data set recorded as the outcome from flipping a coin 100 times, would
follow a normal distribution and may have unknown variances. A t test is
used as a hypothesis testing tool, which allows testing of an assumption
applicable to a population.
Attest looks at the t statistic, the tdistribution values, and the
degrees of freedom to determine the statistical significance. To conduct a
test with three or more means, one must use an analysis of variance.
Attest allows us to compare the average values of the two data
sets and determine if they came from the same population.
Mathematically, the t test takes a sample from each of the two sets and
establishes the problem statement by assuming a null hypothesis that the
two means are equal. Based on the applicable formulas, ce rtain values are
calculated and compared against the standard values, and the assumed null
hypothesis is accepted or rejected accordingly.
If the null hypothesis qualifies to be rejected, it indicates that data
readings are strong and are probably not du e to chance. The t test is just
one of many tests used for this purpose. Statisticians must additionally use
tests other than the t test to examine more variables and tests with larger
sample sizes.
tTest Assumptions
i.The first assumption made regarding t tests concerns the scale of
measurement. The assumption for a t test is that the scale of
measurement applied to the data collected follows a continuous or
ordinal scale, such as the scores for an IQ test.
ii.The second assumption made is that of a simple ra ndom sample,
that the data is collected from a representative, randomly selected
portion of the total population.
iii.The third assumption is the data, when plotted, results in a normal
distribution, bell shaped distribution curve.
iv.The final assumption is the homogeneity of variance.
Homogeneous, or equal, variance exists when the standard
deviations of samples are approximately equal.munotes.in
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84Calculating t Tests
Calculating a t test requires three key data values. They include the
difference between the mean values f rom each data set (called the mean
difference), the standard deviation of each group, and the number of data
values of each group.
The outcome of the t test produces the t value. This calculated t 
value is then compared against a value obtained from a cri tical value table
(called the TDistribution Table). This comparison helps to determine the
effect of chance alone on the difference, and whether the difference is
outside that chance range. The t test questions whether the difference
between the groups re presents a true difference in the study or if it is
possibly a meaningless random difference.
tDistribution Tables
The T Distribution Table is available in onetailandtwo
tailsformats. The one tail is used for assessing cases which have a fixed
value or range with a clear direction (positive or negative). The two tailsis
used for range bound analysis.
TValues and Degrees of Freedom
The t test produces two values as its output : t value and degrees of
freedom. The t value is a ratio of the difference between the mean of the
two sample sets and the variation that exists within the sample sets. While
the numerator value (the difference between the mean of the two sample
sets) is straightforward to calculate, the denominator (the variation that
exists wi thin the sample sets) can become a bit complicated depending
upon the type of data values involved. The denominator of the ratio is a
measurement of the dispersion or variability. Higher values of the t value,
also called t score, indicate that a large dif ference exists between the two
sample sets. The smaller the t value, the more similarity exists between
the two sample sets.
Al a r g et score indicates that the groups are different.
A small t score indicates that the groups are similar.
Degrees of freedom refers to the values in a study that has the freedom to
vary and are essential for assessing the importance and the validity of the
null hypothesis. Computation of these values usually depends upon the
number of data records available in the sample set.
Correlated (or Paired) T Test
The correlated t test is performed when the samples typically
consist of matched pairs of similar units, or when there are cases of
repeated measures. This method also applies to cases where the samples
are related in some ma nner or have matching characteristics, like a
comparative analysis involving children, parents or siblings. Correlated or
paired t tests are of a dependent type, as these involve cases where the two
sets of samples are related.munotes.in
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85The formula for computing t he tvalue and degrees of freedom for
a paired t test is:
Where:
Mean 1 andmean 2 = the average values ofeach ofthesample sets
s (diff) = The standard deviation of the differences of the paired data
values
n = The sample size(thenumber ofpaired differences)
n−1= The degrees offreedom
Equal Variance (or Pooled) T Test
The equal variance t test is used when the number of samples in
each group is the same, or the variance of the two data sets is similar. The
following formula is used for calculating t value and degrees of freedom
for equal variance t test:
Where:
Mean 1 andmean 2 = Average values ofeach of thesample sets
var 1 andvar 2 = Variance ofeach ofthesample sets
n1and n2 = Number ofrecords ineach sample set
And
Degrees ofFreedom =n1+n2−2
where: n1andn2=Number ofrecords ineach sample set
Unequal Variance T Test :
The unequal variance t testis used when the number of sampl es in
each group is different, and the variance of the two data sets is also
different. This test is also called the Welch's t test. The following formula
is used for calculating t value and degrees of freedom for an unequal
variance t test:
Where:
mean 1andmean 2=Average values ofeach of thesample sets
var1andvar2=Variance ofeach ofthesample sets
n1andn2= Number ofrecords ineach sample set
And
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86Where:
var1andvar2=Variance ofeach ofthesample sets
n1andn2=Number ofrecords ineachsample set
II.Ftest :
An “F Test” is a catch all term for any test that uses the F 
distribution . The fstatistic is used in a variety of tests including regression
analysis , the Chow test and the Scheffe Test (aposthocANOVA test).
General Steps for an F Test :
State the null hypothesis and the alternate hypothesi s.
Calculate the F value .
The F Value is calculated using the formula F = (SSE1 –SSE2 /m )/
SSE2 /nk,
Where, SSE = residual sum of squares , m = number of restrictions and k =
number of independent variables.
Find the F Statistic (thecritical value for this test).
The F statistic formula is:
F Statistic = variance of the group means / mean of the within group
variances .
You can find the F Stat istic in the FTable .
Support or Reject th e Null Hypothesis .
F Test to Compare Two Variances :
AStatistical F Test uses an F Statistic to compare two variances ,
s1and s2, by dividing them. The result is always a positive number
(because variances are always positive). The equation for comparing two
variances with the f test is:
F=s2
1/s2
2
If the variances are equal, the ratio of the variances will equal 1.
For example, if we had two data sets with a sample 1( variance of 10) and
a sample 2 (variance of 10), the ratio would be 10/10 = 1.
We a lways test that the population variances are equal when
running an F Test. In other words, always have t o assume that the
variances are equal to 1. Therefore, null hypothesis will always be that the
variances are equal .
Assumptions :
Several assumptions are made for the test.
Population must be approximately normally distributed (i.e. fit the
shape of a bell curve ) in order to use the test.munotes.in
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87The samples must be independent events .
The larger variance should always go in the numerator (the top
number) to force the test into a righttailed test . Right tailed tests
are easier to calculate.
Fortwotailed tests , divide alpha by 2 before finding the
right critical value .
Standard deviations , must be squared to get the variances.
Ifdegrees of freedom aren’t listed in the F Table, use the larger
critical value. This hel ps to avoid the possibility of Type I errors .
III.Z Test
AZtestis a type of hypothesis test —a way to figure ou t if results
from a test are valid or repeatable. For example, if someone said they had
found a new drug that cures cancer, you would want to be sure it was
probably true. A hypothesis test will tell you if it’s probably true, or
probably not true. A Z test, is used when data is approximately normally
distributed (i.e. the d ata has the shape of a bell curve when you graph it).
When can run a Z Test :
Sample size is greater tha n 30. Otherwise, use a t test.
Data points should be independent from each other. In other words,
one data point isn’t related or doesn’t affect another data point.
Data should be normally distributed . However, for large sample
sizes (over 30) this doesn’t always matter.
Data should be randomly selected from a population, where each
item has an equal chance of being selected.
Sample sizes should be equal if at all possible.
Steps to run Z test :
i.State the null hypothesis andalternate hypothesis .
ii.Choose an alpha level .
iii.Find the critical value of z in az table .
iv.Calculate the z test statistic.
v.Compare the test statistic to the critical z value and decide to
support or reje ct the null hypothesis .
Following formula is being used to run Z test.
For the normal population with one sample
munotes.in
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88Where :
x̄=mean of the sample
µis the assumed mean
σisthestandard deviation
nis the number of observations
Two Proportion Z Test :
This tests for a difference in proportions. A two proportion z test
allows to compare two proportions to see if they are the same.
The null hypothesis (H 0) for the test is that the proportions are the
same.
The alternate hypothesis (H 1) is that the proportions are notthe same.
Where
P1and P 2= means of two sample
= overall sample proportion (standard deviation of the sa mple)
n1andn2= numbers of observations of two samples
One sample z test (one tailed z test)
One sample z test is used to determine whether a particular
population parameter, which is mostly mean, significantly different
from an assumed value.
It helps to estimate the relationship between the mean of the
sample and the assumed mean.
In this case, the standard normal distribution is used to calculate
the critical value of the test.
If the z value of the sample being tested falls into the criteria for
theonesided test, the alternative hypothesis will be accepted
instead of the null hypothesis.
A one tailed test would be used when the study has to test whether
the population parameter being tested is either lower than or
higher than some hypothesized valu e.
A one sample z test assumes that data are a random sample
collected from a normally distributed population that all have the
same mean and same variance.
This hypothesis implies that the data is continuous, and the
distribution is symmetric.
Based on th e alternative hypothesis set for a study, a one sided z 
test can be either a left sided z test or a right sided z test.munotes.in
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89For instance, if our H 0:µ0= µ and Ha: µ < µ 0, such a test would be
a one sided test or more precisely, a left tailed test and there i s one
rejection area only on the left tail of the distribution.
However, if H 0:µ=µ 0and Ha: µ > µ 0, this is also a one tailed test
(right tail), and the rejection region is present on the right tail of
the curve.
Two sample ztest(twotailed ztest)
Inthecase oftwosample ztest,twonormally distributed independent
samples arerequired.
Atwotailed ztestisperformed todetermine therelationship between
thepopulation parameters ofthetwosamples.
Inthecase ofthetwotailed ztest, thealtern ative hypothesis is
accepted aslong asthepopulation parameter isnotequal tothe
assumed value.
Thetwotailed testisappropriate when wehave H0:µ=µ0andH0:µ
≠µ0which may mean µ>µ0orµ<µ0
Thus, inatwotailed test, there aretworejectio nregions, oneoneach
tailofthecurve.
Z test sample :
If a sample of 400 male workers has a mean height of 67.47
inches, is it reasonable to regard the sample as a sample from a large
population with a mean height of 67.39 inches and a standard deviat ion of
1.30 inches at a 5% level of significance.
Taking the null hypothesis that the mean height of the population
is equal to 67.39 inches,
we can write:
H0:µ=67.39“
Ha:µ≠67.39“
x=67.47“
σ=1.30“
n=400
Assuming the population to be normal, we can work out the test
statistic zas under:
AsH0is two sided in the given question, we shall be applying a
twotailed test for determining the rejection regions at a 5% le vel of
significance which comes to as under, using normal curve area table:
R:z > 1.96munotes.in
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90The observed value of tis 1.231 which is in the acceptance region since
R: z > 1.96, and thus, H0is accepted .
6.5.2. Non parametric test
Nonparametri c test are also known is distribution free test is
considered less powerful as it uses less information in its calculation and
makes fewer assumption about the data set. A nonparametric test , is which
doesn’t assume anything about the population parameters. Nonparametric
tests include chisquare,Fisher’s exact test and the Mann Whitney test .
When non parametric tests are used
When the study is be tter represented by the median
When the data has a normal distribution
When there is ordinal data, ranked data, or outliers can’t be
removed
When the sample size is very small
When the measurement scale is nominal or ordinal
6.5.3. Chi Square test (X2):
Chi(X2)test is used to determine whether observed data comes
from a given theoretical distribution whether attributes in a given
contingency table are independent and whether the mean values in several
population are same. The Chi (X2) distribution looks like a normal
distribution which is skewed to the right. It is a continuous distribution
which assumes only positive values. It begins at 0 and extended to infinity
in a positive direction.
There are two types of chi square tests . Both use the chi square
statistic and distribution for different purposes:
Where
C = degrees of freedom
O = observed value and
E=expected value
Σ= calculation for every single data item in your data set.
Due to tedious method of calculation most of time following
technology is being used. :
Chi Square Test in SPSS.
Chi Square P Value in Excel.
A chi square statistic is one way to show a relationsh ip between
twocategorical variables . In statistics, there are two types of
variables: numerical (countable) variables andnonnumerical (categorical)
variables . The chi squared statistic is a single number that tells how muchmunotes.in
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91difference exists between observed co unts and the counts expected if there
were no relationship at all in the population.
There are a few variations on the chi square statistic. However, all
of the variations use the same idea, which is comparing expected values
with the values you actually collect. One of the most common forms can
be used for contingency tables :
Where
O = observed value,
E = expected value and
I = “ith” position in the contingency table.
Alow value for chi square means there is a high correlation
between two sets of data. In theory, if observed and expected values were
equal (“no diffe rence”) then chi square would be zero. If the chi square
value is more than the critical value, then there is a significant difference.
The Chi square statistic can only be used on numbers. They can’t
be used for percentages, proportions, means or similar statistical values.
For example, if you have 10 percent of 200 people, you would need to
convert that to a number (20) before you can run a test statistic.
Chi Square P Values.
A chi square test will give a pvalue .T h ep value exhibits that test
results are significant or not. In order to perform a chi squar e test and get
the p value, fowling two pieces of information needed:
i.Degrees of freedom . That’s just the number of categories minu s 1.
ii.Thealpha level (α). This is chosen by the researcher. The usual
alpha level is 0.05 (5%), but could also have other le vels like 0.01
or 0.10.
Degrees of freedom are placed as a subscript after the chi square (Χ2)
symbol. For example, the following chi square shows 6 df :Χ2
6.
And this chi squar e shows 4 df:Χ2
4.
The Chi Square Distribution
The chi square distribution is a special case of the gamma
distribution . A chi square distribution with n degrees of freedom is equal
to a gamma distribution with a = n / 2 and b = 0.5 (or β= 2).
Let’s say you have a random sample taken from a normal
distribution . The chi square distribution is the distribution of the sum of
these random samples squared. Thedegrees of freedom (k) are equal to
the number of samples being summed. For example, if you have taken 10
samples from the normal distribution, then df = 10. The de grees ofmunotes.in
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92freedom in a chi square distribution is also its mean . In this example, the
mean of this particular distribution will be 1 0. Chi square distributions are
always right skewed . However, the greater the degrees of freedom, the
more the chi square distribution looks like a normal distribution.
6.5.4. The ANOVA Test
AnANOVA test is a way to find out if survey or experiment
results are significant . In other words, it helps to figur e out if need to reject
the null hypothesis or accept the alternate hypothesis .
OneWay or Two Way :
Onewayortwowayrefers to the number of independent
variables (IVs) in analysis of Variance test .
Oneway has one independent variable (with 2 levels ). For
example: brand of cereal ,
Twoway has two independent variables (it can have multiple
levels). For example: brand of cereal, ca lories .
Groups or Levels :
Groups or levels are different groups within the same independent
variable . In the above example, levels for “brand of cereal” might be
Lucky Charms , Raisin Bran, Cornflakes —a total of three levels. Levels
for “Calories” might be: sweetened, unsweetened —a total of two levels.
If groups or levels have a hierarchical structure (each level has unique
subgroups), then use a nested ANOVA for the analysis.
Replication :
With a two way ANOVA with replication ,can have two groups
and individuals within that group are doing more than one thing (i.e. two
groups of students from two colleges taking two tests). If only have one
group taking two tests, can use without replication.
6.5.5. Types of Tests :
There are two main types: one way and two way. Two way tests
can be with or without replication.
Oneway ANOVA between grou ps: It is used when to test two
groups to see if there’s a difference between them.
Two way ANOVA without replication: It is used when have one
group and double testing that same group. For example, testing
one set of individuals before and after they take a medication to see
if it works or not.
Two way ANOVA with replication: Two groups , and the members
of those groups are doing more than one thing . For example, two
groups of patients from different hospitals trying two different
therapies.munotes.in
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931) One Way ANO VA :
A one way ANOVA is used to compare two means from two
independent (unrelated) groups using the Fdistribution . The null
hypothesis for the test is that the two means are equal. There fore,
asignificant result means that the two means are unequal.
Examples of one way ANOVA :
Situation 1: You have a group of individuals randomly split into smaller
groups a nd completing different tasks. For example, you might be
studying the effects of tea on weight loss and form three groups: green tea,
black tea, and no tea.
Situation 2: Similar to situation 1, but in this case the individuals are split
into groups based on an attribute they possess. For example, leg strength
of people according to weight. You could split participants into weight
categories (obese, overweight and normal) and measure their leg strength
on a weight machine. The major limitations of the One W ay NOVA test is
that it show that at least two groups were different from each other. But it
won’t shows which groups are different .
2) Two Way ANOVA :
A Two Way ANOVA is an extension of the One Way ANOVA.
With a Two Way ANOVA, there are two independents .T w ow a y
ANOVA is useful when have one measurement variable (i.e. a quanti tative
variable ) and two nominal variables .
For example, to find out if there is an interaction between income
and gender for anxiety level at job interviews. The anxiety level is the
outcome, or the variable that can be measured. Gender and Income are the
twocategorical variables . These categorical variables are also the
independent variables, which are called factors in a Two Way ANOVA.
The factors can be split into levels . In the above example, income level
could be split into three levels: low, middle and high income. Gender
could be split into th ree levels: male, female, and transgender. Treatment
groups are all possible combinations of the factors. In this example there
would be 3 x 3 = 9 treatment groups.
6.5.6. Main Effect and Interaction Effect
The results from a Two Way ANOVA will calculate amain
effect and an interaction effect . The main effect is similar to a One Way
ANOVA: each factor’s effect is considered separately. With the
interaction effect, all factors are considered at the same time. Interaction
effects between factors are easier to test if there is more than one
observation in each cell. For the above example, multiple stress scores
could be entered into cells.munotes.in
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946.6. FACTOR ANALYSIS
6.6.1. Meaning:
Factor analysis is a technique that is used to reduce a large number
of variables into fewer numbers of factors. This technique extracts
maximum common variance from all variables and put s them into a
common score. As an index of all variables, we can use this score for
further analysis. Factor analysis is part of general linear model (GLM) and
this method also assumes several assumptions like :
there is linear relationship,
there is no multi co linearity, it includes relevant variables into
analysis, and
is true correl ation between variables and factors.
6.6.2. Types of factoring:
There are different types of methods used to extract the factor from
the data set:
i.Principal component analysis :This is the most common method used
by researchers. PCA starts extracting the maximum variance and puts
them into the first factor. After t hat, it removes that variance explained by
the first factors and then starts extracting maximum variance for the
second factor. This process goes to the last factor.
ii.Common factor analysis: The second most preferred method by
researchers, it extracts the common variance and puts them into factors.
This method does not include the unique variance of all variables. This
method is used in SEM.
iii.Image factoring: This method is based on correlation matrix. OLS
Regression method is used to predict th e factor in image factoring.
iv.Maximum likelihood method: This method also works on correlation
metric but it uses maximum likelihood method to factor.
v.Other methods of factor analysis: Alfa factoring outweighs least
squares. Weight square is anoth er regression based method which is used
for factoring.
1) Factor loading:
Factor loading is basically the correlation coefficient for the
variable and factor. Factor loading shows the variance explained by the
variable on that particular factor. In the SEM approach, as a rule of
thumb, 0.7 or higher factor loading represents that the factor extracts
sufficient variance from that variable.
2) Eigen values: Eigen values is also called characteristic roots.
Eigenvalues shows variance explained by that pa rticular factor out of themunotes.in
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95total variance. From the commonality column, we can know how much
variance is explained by the first factor out of the total variance.
3) Factor score: The factor score is also called the component score. This
score is of all row and columns, which can be used as an index of all
variables and can be used for further analysis. .
4) Rotation method: Rotation method makes it more reliable to
understand the output. Eigenvalues do not affect the rotation method, but
the rotation method affects the Eigenvalues or percentage of variance
extracted. There are a number of rotation methods available: No rotation
method, Varimax rotation method, Quartimax rotation method,
Directoblimin rotation method, and Promax rotation method.
Assumptions:
i.No outlier: Assume that there are no outliers in data.
ii.Adequate sample size: The case must be greater than the factor.
iii.No perfect multi co linearity: Factor analysis is an interdependency
technique. There should not be perfect multi co linearity between
the variables.
iv.Homoscedasticity: Since factor analysis is a linear function of
measured variables, it does not require homoscedasticity between
the variables.
v.Linearity: Factor analysis is also based on linearity assumption.
Nonlinear variables c an also be used. After transfer, however, it
changes into linear variable.
vi.Interval Data: Interval data are assumed.
6.7. INTERPRETATION OF DATA
6.7.1. Meaning
Data interpretation is the process of reviewing data through some
predefined processes whic h will help assign some meaning to the data and
arrive at a relevant conclusion. It involves taking the result of data
analysis. Data analysis is the process of ordering, categorizing,
manipulating, and summarizing data to obtain answers to research
questi ons. It is usually the first step taken towards data interpretation.
It is evident that the interpretation of data is very important, and as
such needs to be done properly. Therefore, researchers have identified
some data interpretation methods to aid th is process.
6.7.2. Significance of Data interpretation
The purpose of collection and interpretation is to acquire useful and
usable information and to make the most informed decisions possible.munotes.in
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96From businesses, to newlyweds researching their first home, data
collection and interpretation provides limitless benefits for a wide range of
institutions and individuals.
i.It is through interpretation that the researcher can well understand
the abstract principle that works beneath his findings. Through this
he ca n link up his findings with those of other studies, having the
same abstract principle, and thereby can predict about the concrete
world of events. Fresh inquiries can test these predictions later on.
This way the continuity in research can be maintained.
ii.Interpretation leads to the establishment of explanatory concepts
that can serve as a guide for future research studies; it opens new
avenues of intellectual adventure and stimulates the quest for more
knowledge.
iii.Researcher can better appreciate only throu gh interpretation why
his findings are what they are and can make others to understand
the real significance of his research findings.
iv.The interpretation of the findings of exploratory research study
often results into hypotheses for experimental research and as such
interpretation is involved in the transition from exploratory to
experimental research. Since an exploratory study does not have a
hypothesis to start with, the findings of such a study have to be
interpreted on a postfactum basis in which cas e the interpretation
is technically described as ‘post factum’ interpretation.
6.7.3. Data Interpretation Methods
Data interpretation methods are how analysts help people make
sense of numerical data that has been collected, analyzed and presented.
Data, when collected in raw form, may be difficult for the layman to
understand, which is why analysts need to break down the information
gathered so that others can make sense of it.
There are two main methods in which this can be done, namely;
quantitative m ethods and qualitative methods.
1) Qualitative Data Interpretation Method
The qualitative data interpretation method is used to analyse
qualitative data, which is also known as categorical data. This method uses
texts, rather than numbers or patterns to describe data.
Qualitative data is usually gathered using a wide variety of person 
toperson techniques, which may be difficult to analyze compared to the
quantitative research method. Unlike the quantitative data which can be
analyzed directly after it ha s been collected and sorted, qualitative data
needs to first be coded into numbers before it can be analyzed. This is
because texts are usually cumbersome, and will take more time and result
in a lot of errors if analyzed in its original state. Coding done by the
analyst should also be documented so that it can be reused by others and
also analyzed.munotes.in
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97There are two main types of qualitative data, namely; nominal and
ordinal data. These two data types are both interpreted using the same
method, but ordinal dat a interpretation is quite easier than that of nominal
data. In most cases, ordinal data is usually labelled with numbers during
the process of data collection, and coding may not be required. This is
different from nominal data that still needs to be coded for proper
interpretation.
2) Quantitative Data Interpretation Method
The quantitative data interpretation method is used to analyze
quantitative data, which is also known as numerical data. This data type
contains numbers and is therefore analyzed with the use of numbers and
not texts.
Quantitative data are of two types namely; discrete and continuous
data. Continuous data is further divided into interval data and ratio data,
with all the data types being numeric. Due to its natural existence as a
numbe r, analysts do not need to employ the coding technique on
quantitative data before it is analyzed. The process of analyzing
quantitative data involves statistical modelling techniques such as standard
deviation, mean and median.
6.7.4. Precautions in Data interpretation
It must be always remember that even if the data are properly
collected and analyzed, wrong interpretation would lead to inaccurate
conclusions. It is, therefore, absolutely essential that the task of,
interpretation be accomplished with pa tience in an impartial manner and
also in correct perspective. Following precautions need to be taken in data
interpretation.
i.Identify the Required Data Type
Researchers need to identify the type of data required for particular
research. It may be nominal, ordinal, interval, or ratio data . The key to
collecting the required data to conduct research is to properly understand
the research question. If the resea rcher can understand the research
question, then he can identify the kind of data that is required to carry out
the research.
ii.Avoid Biases
There are different kinds of biases a researcher might encounter
when collecting data for analysis. Although biases sometimes come from
the researcher, most of the biases encountered during the data collection
process is caused by the respondent.
There are two main biases, namely, response bias and non 
response bias . Researchers may not be able to eliminate these biases, but
there are ways in which they can be avoided and reduced to a minimum.
Response biases are biases that are caused by respondents intentionally
giving wrong answers to r esponses, while non response bias occurs whenmunotes.in
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98the respondents don't give answers to questions at all. Biases are capable
of affecting the process of data interpretation .
iii.Use Close Ended Surveys
Although open ended surveys are capable of giving detailed
information about the questions and allow respondents to fully express
themselves, it is not the best kind of survey for data interpretation. It
requires a lot of coding before the data can be analyzed.
Close ended surveys , on the other hand, restrict the respondents'
answer to so me predefined options, while simultaneously eliminating
irrelevant data. This way, researchers can easily analyze and interpret
data.
However, close ended surveys may not be applicable in some
cases, like when collecting respondent's personal information like name,
credit card details, phone number, etc.
iv.Researcher must invariably satisfy himself that (a) the data are
appropriate, trustworthy and adequate for drawing inferences; (b) the
data reflect good homogeneity; and that (c) proper analysis has been
done through statistical methods.
v.The researcher must remain cautious about the errors that can possibly
arise in the process of interpreting results.
6.8. SUMMARY:
The statistics vary based on whether the study is a between 
participants or correlated groups design. It is imperative that the
appropriate statistic be used to analyze the data collected in an experiment.
The first point to consider when determining which statistic to use is
whether it should be a parametric or nonparametric statistic. This de cision
is based on the type of data collected, the type of distribution to which the
data conform, and whether any parameters of the distribution are known.
The second consideration is whether a between participants or correlated 
groups design has been u sed. This information enables us to select and
conduct the statistical test most appropriate to the particular study’s design
and data.
6.9. EXERCISE:
A. Test your knowledge by choosing the correct option:
1. …………….is a statistic that measures the degre e to which two
variables move in relation to each other. (mean deviation ,Correlation ,
standard deviation, Regression)
2. The …………..coefficient's values range between 1.0 and 1.0. (Mean
deviation ,Correlation , standard deviation, Regression)munotes.in
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993. A pe rfect positive correlation means that the correlation coefficient is
exactly…. ( 1, 1, 0, 0.5)
4. When price of a commodity increases its demand goes down or vice 
versa, its ………. correlation (Positive, Negative, Partial, Multiple)
5. Which method is a d iagrammatic representation of a bivariate
distribution for ascertaining the nature of correlation between the
variables? (Scatter diagram, Regression lines, mean deviation ,standard
deviation)
6. …………………is an act in statistics whereby an analyst tests an
assumption regarding a population parameter. (Hypothesis testing, Scatter
diagram, Regression lines, mean deviation)
7. A statistical hypothesis which under test is usually a hypothesis o f no
difference and hence is called …..hypothesis. (Alternative, Null, Second,
negative)
8. A hypothesis which is accepted when H 0is rejected is called
………..hypothesis. (Alternative, Null, Second, negative)
9. ………………test are also known is distribution free test. (Parametric,
Nonparametric, Two sample , Paired T test)
10. A ………….is a type of inferential statistic used to determine if there
is a significant difference between the means of two groups. ( t test,F test,
chi Square, ANOVA)
11. ………………. refers t o the values in a study that has the freedom to
vary and are essential for assessing the importance and the validity of the
null hypothesis. ( Power of test, Parametric tests, Degrees of freedom,
Null hypothesis )
12. Which test is used to determine whether observed data comes from a
given theoretical distribution whether att ributes in a given contingency
table are independent and whether the mean values in several population
are same? (F test, test, Chi (X2), ANOVA)
13. The …………… distribution is a special case of the gamma
distribution . (F test, test, Chi (X2), ANOVA)
14. ……………………….. helps to figure out if need to reject t he null
hypothesis or accept the alternate hypothesis . (F test, test, Chi (X2),
ANOVA)
15.A ………… ANOVA is used to compare two means from two
independent (unrelat ed) groups usingthe Fdistribution . (one way, two
way, Replication, Groups)
16. …………… analysis is a technique that is used to reduce a large
numbe r of variables into fewer numbers of factors. (One way ANOVA,
Two way ANOVA, Factor, Replication)
17. ………………is the process of reviewing data through some
predefined processes which will help assign some meaning to the data andmunotes.in
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100arrive at a relevant conclusi on. (Data interpretation, Data collection,
Hypothesis, Review of literature)
18. The qualitative data interpretation method is used to analyse …….data
(Numerical, categorical, Statistical)
(Answers : 1. Correlation, 2. Correlation, 3. 1, 4. Negative, 5. S catter, 6.
diagram, 7.Hypothesis testing, 8. Null, 9. Alternative, 10. Nonparametric,
11. t test, 12. Degrees of freedom, 13. Chi (X2), 14. Chi (X2), 15.
ANOVA, 16. one way, 17. Factor, 18 Data interpretation, 19. Categorical)
B. Short Answer Questions:
1. Explain the concept correlation
2. Elaborate the types of correlation.
3. Explain the different shapes of Scatter diagram
4. Define line of regression
5. Which are the Properties of Regression coefficients?
6. Explain the level of significance.
7. Di fferentiate between Type I and Type I errors.
8. Explain the one tailed and two tailed test.
9. Explain the Parametric tests.
10. Which are the assumptions of t Test?
11. Which are the General Steps for an F Test?
12. Explain the concept of Z test.
13. Explain two way ANOVA.
14. Identify the different types of factoring.
15. Which Precautions are needed in Data interpretation?
6.10 REFERENCE
I.Sherri L. Jackson, (2009) , Research Methods and Statistics, A
Critical Thinking Approach, ISBN 13: 978 049551001 7
II.BASIC ECONOMETRICS,(2003) Damodar N. Gujarati, McGraw 
Hill Higher Education ISBN: 978 007233542 2
III.Sachdeva J.K.(2011). Business Research Methodology. New
Delhi: Himalaya Publishing House.
IV.Michael V.P.(1997). Research Methodology in Managem ent.
Delhi: Himalaya Publishing House
munotes.in
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101Module IV
RESEARCH REPORT AND MODERN PRACTICES IN
RESEARCH
7
RESEARCH REPORT
Unit structure
7.0Objectives
7.1 Introduction
7.2 Structure of the research report
7.3 References and Citation Methods
7.4 References
7.5 Footnotes
7.6 Bibliography
7.7 Summary
7.8 Exercise
7.9 Reference
7.0 OBJECTIVES
To understand essentials of research report writing.
To study different structures and layout used for report writing.
To differentiate between footnote and bibliography.
To know different styles o f references and citation methods.
7.1 INTRODUCTION:
7.1.1 Meaning
The research work is presented in a written form. The practical
utility of research study depends heavily on the way it is presented to
those who are expected to act on the basis of resea rch findings. Research
report is a written document containing key aspects of research project.
Research report is a medium to communicate research work with relevant
people. It is also a good source of preservation of research work for the
future referenc e. Many times, research findings are not followed because
of improper presentation. Preparation of research report is not an easy
task. It is an art. It requires a good deal of knowledge, imagination,
experience, and expertise. It demands a considerable ti me and money.
A research report is a document prepared by an analyst or strategist
who is a part of the investment research team in a stock brokerage ormunotes.in
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102investment bank. A research report may focus on a specific stock or
industry sector, a currency, commo dity or fixed income instrument, or on
ageographic region or country. Research reports generally, but not always,
have actionable recommendations such as investment ideas that investors
can act upon.
7.1.2 Essentials of research report:
Report writing d iffers from person to person depending on
personality, imaginative and creative abilities, experience, and training.
However, most researchers agree that following general principles must be
kept in mind to produce a better research report. These principle s are often
called as qualities or requirements of a good report.
1.Accuracy: The information collected and presented by the researcher
must be accurate to the best of his knowledge. Wherever, possible the
sources of data can be mentioned to make report more authentic. The
consistency must be maintained while writing report it includes the
data, language and also the presentation.
2.Concise: The research report must be concise, brief and straight to the
point. Irrelevant topics can be avoided. There is no mini mum or
maximum limit of pages that report should consist. Hence, a
researcher can stick to the research topic and cover the pointers
related to that.
3.Logical arrangement : As such there is no standard format to be
followed for writing a research project y et, researcher needs to take
care that there is a proper flow and logical connectivity among
chapters. Eg: Conclusions and suggestions of the study will follow
only after the analysis and interpretation of the data.
4.Date and signature: These two are the im portant elements of the
research report and therefore its existence in research report makes
the report more concrete. It also helps new researchers to know the
period of the study. The signatures of officials and researchers makes
the report more reliable .
5.Impersonal style of writing: The researcher needs to write a research
report in “third form” i.e. without using the words like I, me, you, we
etc. The language used must be decent and official. Informal words,
expressions must be avoided. No need to use sophisticated language
even a simple language can serve the purpose of communicating
research outcomes to readers.
6.Timely submission of report: For every research report a particular
time frame is allotted and researcher must stick to that time. It
requir es proper planning and allocation of work so that the research
repot can be completed in a given time frame.munotes.in
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1037.References: This is the most important section of research report. The
researcher refers several research works, books, research papers etc
and re searcher may take some content from same, hence, the credit
must be given to all those authors and publishers. Thus, references
must be mentioned at the end of the research project.
8.Attractive presentation: If research report contains only text and
data, the reader will not be interested to read in detail. Hence,
wherever possible, data must be converted in colourful charts and
pointers or variables can be put forward in the form of diagrams. It
will attract the attention of readers.
7.1.3 Significance of research report:
1.Decision Making Tool: Today’s complex business organizations
require thousands of information. Â reports provide the required
information a large number of important decisions in business or any
other area are taken on the basis of in formation presented in the
reports. This is one of the great importance of report.
2.Transmission of knowledge : The knowledge that has been obtained
on the basis of research need transmission for proper utilization of the
resources invested. Because of that reason, it is always advisable to
prepare to report in a written manner so that it can also provide
knowledge to layman in understanding various social problems.
3.Investigation: Whenever there is any problem, a committee or
commission or study group investi gates the problem to find out the
reason behind the problem and present the findings with or without the
recommendation in the form of a report.
4.Inspiration for Further Research: Research report inspires others to
undertake further research in the same li ne or in any other inter 
disciplinary fields. If the report appears to be interesting and a novel
one, it is more likely to draw the attention of the social scientists.
5.Evaluation: Large scale organizations are engaged in
multidimensional activities. It is not possible for a single top executive
to keep personal watch on what others are doing.
So, the executive depends on reports to evaluate the performance of
various departments or units.
6.Development of skill: Report writing skill develops the power of
designing, organization coordination, judgment and communication.
7.Presentation of finding: Society is more concerned with the finished
product in terms of output of research which has the input of immense
money, human resources and precious time. Therefore, t he socialmunotes.in
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104utility of the research report lies in its exposure to the layman as well
as submission to the sponsoring agency.
8.Professional Advancement: Report also plays a major role in
professional achievement. For promotion to the rank andfile position,
satisfactory job performance is enough to help a person. But for
promotion to high level position, intellectual ability is highly required.
Such ability can be expressed through the report submitted to higher
authority.
9.A managerial Tool: Various reports m ake activities easy for the
managers. For planning, organizing, coordinating, motivating and
controlling, manager needs help from a report which acts as a source
of information.
10.Encountering Advance and Complex Situation: In a large business
organizati on, there is always some sort of labor problems which may
bring complex situations. To tackle that situation, managers take the
help of a report.
7.2 STRUCTURE OF THE RESEARCH REPORT:
7.2.1 Meaning
Research reports are recorded data prepared by researc hers or
statisticians after analyzing information gathered by conducting
organized research. A research report is a reliable source to recount
details about a conducted research and is most often considered to be a
true testimony of all the work done to ga ther details of research.
Researchers can prepare report at their ease as there are no such set rules
or procedure of writing reports. However, following general guidelines
can help for writing research reports:
7.2.2 Preliminary content:
1. A certi ficate stating the details of university/institution where the
research project is to be submitted. The certificate must be duly signed
by researches and research guide.
2.Acknowledgement: Researcher should take this as an opportunity to
thank all those p eople who have helped to conduct the research work
successfully. Eg: Statistician for statistical help, respondents for filling
up the forms, etc.
3.Table of content : It is also known as an Index. This will help the reader
to trace the content on the giv en page number.
4.List of tables and graphs : Tables and graphs are part of every research
and thus a separate index can be prepared mentioning the table and
chart displayed on a particular page.munotes.in
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1055.Abbreviations: There are certain words which are used r epetitively in
the report and thus, an abbreviation can be used instead of writing a
complete word. The list of abbreviations used by researcher must be
given at the preliminary stage, so that, reader gets an idea.
7.2.3 Body of the report:
Chapter 1 –Introduction
This is the first chapter of the research work, wherein the reader is
introduced to the basis of the research topic. The reader gets an idea
about the complete work from this chapter.
This chapter may consist of following points:
Objectives o f the study
Significance of the study
Scope of the study
Limitations of the study
Origin of the study
Chapter scheme of the research
Chapter 2 Review of literature:
This chapter consists of a brief summary framed by researcher about
the past research or studies done by other researchers. It may include
research done at national or international level as well. This chapter
will help the reader to know the past contributions made by similar
researchers.
Chapter 3 –Research methodology
In this chapter, a complete process and research tools are used in
research is been highlighted. It includes:
Hypotheses of the research work.
A brief report on pilot study
Reliability check of questionnaire
Conceptual framework, if relevant to the topic
Research design
Population and Sample size
Techniques used for data analysis in research process.
Description of questionnaire.

Chapter IV –Core concept/ Population of the research
This chapter includes a complete information about a core concept
selected by the resear cher to conduct research. Eg: Research topic: A
study on causes and effects of stress among youth. In this case, a
separate chapter can be framed on Stress (Core concept) and another
chapter can be framed on Youth (Population). The chapter may
include:
Meaning of stress
Causes of stress
Impact of stress
Symptoms of stress
Theory put forward by earlier researchers.munotes.in
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106Chapter V –Findings and observations
This chapter is the heart of the research project as it consists of a
compilation of data collected by r esearcher. The data is presented in a
form of tables and charts as it becomes easy for a stranger to relate it
to the topic. Wherever, required justification and interpretation of the
presented data must be given. Researcher can also write their
observatio n that they come across while interacting with respondents.
This chapter also gives the explanation for the hypothesis and
objectives framed by the researcher.
Chapter VI –Conclusion and suggestions
The complete research process is undertaken to come up with this
chapter. In this chapter, researcher gives suggestions based on
analysis and data collected by the researcher. A concrete conclusion
to sum up the topic must also be framed in this chapter. Researchers
can link their suggestion with theories or they can come up with their
own model in the form of suggestion.
Chapter VII –Road ahead
This is the last chapter of the project, wherein, researcher chalks out
the area which is not covered and there is a scope for future
researchers to do in depth stud y. This chapter is very brief and concise
in nature.
7.2.4 Supplementary material
This section includes all those extra documents used for conducting
research must be attached and described. It includes following
documents:
a. Questionnaire:
Every rese archer uses a questionnaire to collect primary data from
respondent. A copy of questionnaire must be attached. If the
questionnaire, is translated in different language then questionnaire in
both the languages must be attached.
b. Letters:
If the researcher has received any letters from companies or
respondent, the same must be attached at the end of the report. If
researcher has submitted any letters for the process of data collection,
same can be attached at the end.
c. Report of plagiarism ch eck:
Nowadays plagiarism check is must and therefore, every researcher
needs to attach a plagiarism certificate, stating the content is authentic
and first hand. Many software are available, researcher can have a
plagiarism check and get the certificate .munotes.in
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1077.2.5 References/ Bibliography:
All those books, research papers, sites, newspapers referred by
researcher needs to be mentioned under this heading. All these
references must be mentioned in different categories in alphabetical
manner. It becomes a huge source of references for new researchers to
refer.
7.2.6 Images:
Although, this section is optional but, if research demands images,
those can be included under this section with proper heading and brief
description. It can make the research more interesting and attractive.
7.3 REFERENCES AND CITATION METHODS:
7.3.1 Meaning:
A citation is a way of giving credit to individuals for their creative
and intellectual works that is been utilized by a researcher for the work. It
can also be used to lo cate particular sources and combat plagiarism.
Typically, a citation can include the author's name and date. A citation
style dictates the information necessary for a citation and how the
information is ordered, as well as punctuation and other formatting. A
citation tells the readers where the information came from.
The citation can be maintained in three forms, they are as under:
a. The name andyear system
Citations: When researcher cite the source of information in the report,the
names of the authors and the date of publication is mentioned.
Jenkins and Busher (1979) report that beavers eat several kinds of
herbaceous plants as well as the leaves, twigs, and bark of most species of
woody plants that grow near water.
Beavers have been shown to be discri minate eaters of hardwoods
(Crawford, Hooper, and Harlow 1976).
b. The alphabet number system.
Citations: When researcher cite the source of information in the report, a
number in parentheses are given that corresponds to the number of the
source in the alphabetical listing in the "References."
Jenkins and Busher report that beavers eat several kinds of herbaceous
plants as well as the leaves, twigs, and bark of most species of woody
plants that grow near water (4).
Beavers have been shown to be discrimin ate eaters of hardwoods (3).
7.3.2 The Citation Order System (typically used in engineering IEEE
documentation).munotes.in
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108Citations: When researcher cite the sources of information in the report, a
given number in brackets that corresponds to the number of the so urce
listed in the order in which they appear in the report, the source listed first
as [1], the next source [2], etc.
Jenkins and Busher report that beavers eat several kinds of herbaceous
plants as well as the leaves, twigs, and bark of most species of w oody
plants that grow near water [1].
Beavers have been shown to be discriminate eaters of hardwoods [2].
7.4 REFERENCES:
7.4.1 Meaning
A reference gives the readers details about the source so that they
have a good understanding of what kind of so urce it is and could find the
source themselves if necessary. The references are typically listed at the
end of the research report.
7.4.2 APA style:
APA is the style of documentation of sources used by the
American Psychological Association. This form o f writing research papers
is used mainly in the social sciences, like psychology, anthropology,
sociology, as well as education and other fields.Citation in the research reportmunotes.in
Page 109
109Material Type Intext Citation BibliographyA book (Sapolsky,
2017)Sapolsky, R. M.
(2017). Behave: The bio logy
of humans at our best and
worst . Penguin Books.Chapter in
anedited book
(If the chapter is
from an authored
book, use the
book citation )(Dillard, 2020) Dillard, J. P. (2020).
Currents in the study of
persuasion. In M. B. Oliver,
A. A. Raney, & J. Bryant
(Eds.), Media effects:
Advances in theory and
research (4th ed., pp. 115 –
129). Routledge.An article in a
print journal(Weinstein,
2009)Weinstein, J. (2009). “The
market in Plato’s
Republic.” Classical
Philology ,104(4), 439 458.An article in an
electronic journal(Grady et al.,
2019)Grady, J. S., Her, M.,
Moreno, G., Perez, C.,
&Yelinek, J. (2019).
Emotions in story books: A
comparison of storybooks
that represent ethnic and
racial groups in the United
States. Psychology of
Popular Media
Culture ,8(3), 207 –
217. https://doi.org/10.1037/
ppm0000185A website (Bologna, 2019) Bologna, C. (2019, October
31).Why some peopl ew i t h
anxiety love watching horror
movies .
HuffPost. https://www.huffp
ost.com/entry/anxiety love
watching horror 
movies_l_5d277587e4b02a5
a5d57b59e
Source: https://pitt.libguides.com/citationhelp/ apa7
7.4.3 Chicago style:
Chicago is a documentation style that has been published by the
Chicago University Press since 1906. This citation style incorporates rules
of grammar and punctuation common in American English. Typically,
Chicago style presents two basic documentation systems:munotes.in
Page 110
110(1) Notes and bibliography
(2) Author date.
Choosing between the two often depends on subject matter and the
nature of sources cited, as each system is favored by different groups of
scholars. The notes and bibliography style is preferred by many in the
humanities, including those in literature, history, and the arts. This style
presents bibliographic information in notes and, often, a bibliography.
Material Type Notes/Bibliography StyleA book in print Note Style: 1.Michael Pollan, The Omnivore's
Dilemma: A Natural History of Four
Meals (New York: Penguin, 2006), 99 –100.
Duplicate Note: 2. Pollan, Omnivore's
Dilemma, 3.
Bibliography: Pollan, Michael. The Omnivore's
Dilemma: A Natural History of Four Meals .N e w
York : Penguin, 2006.An article in a
print journalNote Style: 1. Joshua I. Weinstein, "The Market
in Plato’s Republic ,"Classical Philology 104
(2009): 440.
Duplicate Note: 2. Weinstein, "Plato’s Republic ,"
452–53.
Bibliography: Weinstein, Joshua I. "The Mar ket
in Plato’s Republic ."Classical Philology 104
(2009): 439 –58.An article in an
electronic journalNote Style : 1. GueorgiKossinets and Duncan J.
Watts, “Origins of Homophily in an Evolving
Social Network,” American Journal of
Sociology 115 (2009): 411, accessed February
28, 2010, doi:10.1086/599247.
Duplicate Note: Kossinets and Watts, “Origins of
Homophily,” 439.
Bibliography: Kossinets, Gueorgi, and Duncan J.
Watts. “Origins of Homophily in an Evolving
Social Network.” American Journal of
Sociology 115 (2009): 405 –50. Accessed
February 28, 2010. doi:10.1086/599247.A website Note Style: 1.“Google Privacy Policy,” last
modified March 11, 2009,
http://www.google.com/intl/en/privacypolicy.ht
ml.
Duplicate Note: “Google Privacy Policy.”
Bibliography: Googl e. “Google Privacy Policy.”
Last modified March 11, 2009.
http://www.google.com/intl/en/privacypolicy.ht
ml.
Source: https://pitt.libguides.com/citationhelp/chicagomunotes.in
Page 111
111Theauthor date style has lo ng been used by those in the physical,
natural, and social sciences. In this system, sources are briefly cited in the
text, usually in parentheses, by author’s last name and date of publication.
The short citations are amplified in a list of references, wh ere full
bibliographic information is provided.
Author/Date
StyleIntext Citation Bibliography
A book (Pollan 2006,
99–100)Pollan, Michael. 2006. The
Omnivore’s Dilemma: A
Natural History of Four
Meals . New York: Penguin.
An article in a
print journa l(Weinstein 2009,
440)Weinstein, Joshua I. 2009.
“The Market in
Plato’s Republic .”Classical
Philology 104:439 –58.
An article in an
electronic
journal(Kossinets and
Watts 2009,
411)Kossinets, Gueorgi, and
Duncan J. Watts. 2009.
“Origins of Homophily i na n
Evolving Social
Network.” American Journal
of Sociology 115:405 –50.
Accessed February 28, 2010.
doi:10.1086/599247.
A website (Google 2009) Google. 2009. “Google
Privacy Policy.” Last
modified March 11.
http://www.google.com/intl/e
n/privacypolicy.htm l.
Source: https://pitt.libguides.com/citationhelp/chicago
7.4.4 MLA Style:
MLA (Modern Language Association) style for documentation is
widely used in the humanities, especially in writing o n language and
literature. MLA style features brief parenthetical citations in the text keyed
to an alphabetical list of works cited that appears at the end of the work.
Material Type Works Cited
Book in print Card, Claudia. The Atrocity Paradigm: A
Theo ry of Evil . Oxford UP, 2005.
eBook Gaither, Milton. Homeschool: An American
History. Palgrave Macmillan,
2017. SpringerLink ,doi
org.pitt.idm.oclc.org/10.1057/978 1349
95056 0.munotes.in
Page 112
112An article in a print
journalDoggart, Julia. "Minding the Gap: Realizing
Our Ideal Community Writing Assistance
Program." The Community Literacy
Journal, vol. 2, no. 1, 2007, pp. 7180.
An article in an
electronic journalSherrard Johnson, Cherene. "'A Plea for
Color': Nella Larsen's Iconography of the
Mulatta." American Liter ature , vol. 76, no. 4,
2004, pp. 833 869, doi: 10.1215/00029831 76
4833.
A encyclopaedia
entry“Patanjali.” Benét’s Reader’s Encyclopedia ,
edited by Bruce Murphy, 4th ed.,
HarperCollins Publishers, 1996, p. 782.
A government
publicationUnited States, Federal Maritime
Commission. Hawaiian Trade Study: An
Economic Analysis . Government Printing
Office, 1978.
An interview you
conductedBrandt, Deborah. Personal interview. 28 May
2008.
(Note: List the interview under the name of the
interviewee)
Af i l m / D VD Note: This depends on the focus of your work.
Please see the MLA Style blog for a detailed
explanation.
A Page on a Website
with no author"Stunning Lakeside View on Lake
Erie." VisitPA, Com monwealth of
Pennsylvania, 7 June 2018,
www.visitpa.com/article/stunning lakeside 
views lakeerie.
A Page on a Website
with an authorDel Castillo, Inigo. "How Not to Kill Your
Houseplants, According to
Botanists." Apartment Therapy, 29 Jan. 2020,
www.apa rtmenttherapy.com/houseplant tips
botanists 36710191.
Artwork from
websiteSherald, Amy. Former First Lady, Michelle
Obama . 2018. National Portrait Gallery ,
npg.si.edu/object/npg_NPG.2018.15.
Source: https://pitt.libguides.com/citationhelp/mla8thedition
7.5 FOOTNOTES:
7.5.1 Meaning
While preparing research report the materials, books, articles,
published or unpublished material etc should be given propermunotes.in
Page 113
113acknowledgement by way of foo tnotes and bibliography. Oxford
Dictionary refers report as an ascertained fact of record.
Footnotes are used to give the credit for borrowed words, ideas,
symbols or other forms of expression should be given and their sources
should be stated in the tex t or footnotes. Footnotes are of two kinds they
are as follows:
Content notes
Reference notes
The objectives of having footnotes in research project are as follows:
1.To acknowledge in the author of original work
2.To refer the source of information and to establish the validity of
evidence.
3.To amplify or clarify the ideas or information presented in the text.
4.To give original version of material.
5.To provide cross reference to various parts of thesis.
The name and complete detail form where the informati on and
paragraph has been taken is given in footnotes. If the information is on one
single page it could be preceded by “P”. If it is on two or more pages it
could be “PP”. Following format of footnotes must be followed:
Examples of footnotes are as fol lows:
A)Citing Book:
1.Mann, Social change and social research, New Delhi, concept
publishing company, 1988. P –25.
2.Ibid, PP 20 –24
B)Newspaper articles:
1.Kumar, Naresh, “Exploring sea for economic progress”, The
Economic Times (Bangalore) August 8, 1989. P –6.
2.Kamal Shal, “Effects of recession on corporate world”. The Times
of India (Mumbai), March 8, 2009.
C)Research papers:
1.Mr. Irshad. I and Bhat. Apresented and published the paper “The
vitality and role of Self Help Group (SHGS) in women upliftment:
Special reference to Kashmir” in International Journal of Research
–Granthaalyah. Vol.3 Issue.8 in the year 2015.munotes.in
Page 114
114D)Citing Thesis or dissertation:
1.Bangalore: Indian Institute of Science, 1986.
E)Publications of Government and public organisations:
1.World Bank, Ru ral development sector policy paper, Washington
DC, 1975. P –26.
F)Internet and websites:
https://mavimindia.org/
7.6 BIBLIOGRAPHY:
7.6.1 Meaning
This is the first terminal item presented at the end of the report.
The bibliography contains the list of books, articles, and magazines etc
which were referred by reporter while preparing research report. The list is
presented at the end of the report. The list must be in alphabetical order.
Hence, it becomes easy to find and identify particular book or articles.
Alternatively, the list of names could be grouped like:
Bibliography is different from footnotes. Footnotes are placed at
the end of the page at the bottom. Whereas, on the other hand bibliography
are placed at the end of the report. In bibliography name of author is
written later and surname is written first. Eg: Drucker, Peter. E
The functions of bibliography are different from footnotes.
Bibliography gives the identification detail, as a whole. Footnotes give the
complete detail about from where the information has been taken.
Bibliography does not displace exact place i.e. page number. A
bibliography containing less than 20 lines need not be subdivided into
categories. They could be written one below the:
A)Books:
1.Bulmer Martin, Sociological Research Methods, London, 1977,
Macmillan.
2.Brislin, Cross –Culture Research Methods, New York, John Wiley
and sons, 1973.
B)Reports
1.World Bank, World Development Report 1987, Washington.
2.United Nations, 1984.
3.UNCTAD, The l east Development countries, 1984.munotes.in
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115C)Journals
1.Das.D, Das.Band Mitra. S (2017). Impact of Women
Participation in SHGs for Their Empowerment and Livelihood
in Belbari Block of West Tripura District, Tripura, India.
International Journal of Research in Geograp hy (IJRG).
Volume 3, Issue 3. PP 60 68.
2.Kamalanathan. K. (2016). Women empowerment and
microfinance –A study on Self Help Groups in Thane district
of Maharashtra. Scholarly Research Journal for
Interdisciplinary Studies. Vol 4.25. PP 2449 –2457.
7.7 SUMMARY
This chapter highlights the process and essentials of compiling all the
research oriented data and putting it in the right order and making a
complete research report of it. The report can be divided into several parts
and that is explained in a process format in detailed manner. Writing a
research report is an art and thus every researcher needs to possess those
skills and techniques. The difference between Bibliography and
References has been explained as they play a vital role in every res earch
report. There are different ways to cite the research work that has been
reviewed by researchers and the same has been explained with suitable
examples.Difference between Footnote and Bibliographymunotes.in
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1167.8 EXERCISE
Practice questions:
1. Explain the layout of research report in detail.
2. Brie fly explain the essentials of research report.
3. Describe the importance of research report.
4. What is references? Explain different styles of references.
5. Elaborate the difference between footnote and bibliography with
suitable examples.
Fill in t he blanks
1.Table of content is also known as ____________.
2.___________________ consist of a brief summary framed by
researcher about the past research or studies done by other
researchers.
3.Questionnaire is used to collect ______________ data from
respondent s.
4.A ___________is a way of giving credit to individuals for their
creative and intellectual works that is been utilized by a researcher
for the work.
Answers: 1. Index 2. Review of literature 3. Primary 4. Citation
True or False:
1.Footnote and Bibliogr aphy are different. –True
2.Review of literature is based on secondary data –True
3.Chapter: Analysis and interpretation consist of tables and graphs
explaining primary data –True
4.Bibliography is always mentioned in the beginning of the report –
False
7.9 REFERENCE
1. C. R. Kothari. Research Methodology: Methods & techniques. 2nded.
2. P.S.S. Sunder Rao, J. Richard.Introduction to Biostatistics and Research
Methodology. 4thed.
https://la bwrite.ncsu.edu/res/res citsandrefs.html
https://pitt.libguides.com/citationhelp/apa7
https://www.slideshare.net/Shru tiMishra19/ppt onreport writing
http://www.jiwaji.edu/pdf/ecourse/economics/Research%20Report.pdf
munotes.in
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1178
MODERN PRACTICES IN RESEARCH
Unit Structure
8.0 Objective
8.1 Introduction
8.2 Role of Computers in Research
8.3 Ethical Norms in Research
8.4 Plagiarism in Research
8.5 Summary
8.6 Exercise
8.7 References
8.0OBJECTIVE
To understand modern methodologies used in research.
To make out the role of companies in research.
To recognize ethical norms in research.
To comprehend the plagiarism checks in research.
8.1INTRODUCTION
The role of research in several fields whether related to business or
to the economy as a whole, has greatly increased in modern times . The
increasingly complex nature of business and government has focused
attention on the use of research in solving operational problems. Research,
as an aid to economic policy, has gained added importance, both for
government and business.
Usage of tech nology and different software has made the work of
researchers more easy and interesting. Moreover, the data and studies of
different researcher can be easily reviewed and re worked on it.
For instance, government’s budgets rest in part on an analysis of
the needs and desires of the people and on the availability of revenues to
meet these needs. The cost of needs has to be equated to probable
revenues and this is a field where research is most needed. Through
research we can devise alternative policies an d can as well examine the
consequences of each of these alternatives.munotes.in
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1188.2 ROLE OF COMPUTERS IN RESEARCH
8.2.1 MEANING
The computers are indispensable throughout the research process.
The role of computer becomes more important when the research is on a
large sample. Data can be stored in computers for immediate use or can be
stored in auxiliary memories like floppy discs, compact discs, universal
serial buses (pen drives) or memory cards, so that the same can be
retrieved and easily accessible from eve rywhere. The usage of computer
has made the job of researcher easier due to the speed in working and high
level of accuracy level. The new software has made the things easier to
understand and implement.
The computers assist the researcher throughout dif ferent phases of
research process. There are five major phases of the research process.
They are:
A. Conceptual phase
B. Design and planning phase
C. Empirical phase
D. Analytic phase
E. Dissemination phase
A. ROLE OF COMPUTER IN CONCEPTUAL PHASE :
The conceptual phase consists of formulation of research problem,
review of literature, theoretical frame work and formulation of hypothesis.
Computers help for searching the literatures (for review of literature) and
bibliographic references stored in the e lectronic databases of the
worldwide webs. The articles published in international journals can also
be accessed through computers. There are different portals available where
the researches of earlier scholars are uploaded for reference purpose. It can
thus be used for storing relevant published articles to be retrieved
whenever needed. This has the advantage over searching the literatures in
the form of books, journals and other newsletters at the libraries which
consume considerable amount of time and ef fort. The MS Word also
helps the researcher to put references in the required style.
B.ROLE OF COMPUTERS IN DESIGN AND PLANNING PHASE:
Design and planning phase consist of research design, population,
research variables, sampling plan, reviewing rese arch plan and pilot study.
Role of Computers for Sample Size Calculation: Several software are
available to calculate the sample size required for a proposed study.
NCSS PASS GESS is such software. The standard deviation of the data
from the pilot study is required for the sample size calculation. Usage of
MsExcel can help the researcher to sort, analyse and present the data as
per requirement. Basic statistical techniques like chi square, correlation,
etc and also be implemented with the add on features of Megastat.munotes.in
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119C. ROLE OF COMPUTERS IN EMPIRICAL PHASE:
Empirical phase consist of collecting and preparing the data for
analysis. The data obtained from the respondents are stored in computers
as word files or excel spread sheets. This has the advanta ge of making
necessary corrections or editing the whole layout of the tables if needed,
which is impossible or time consuming incase, of writing in papers. Thus,
computers help in data entry, data editing, data management including
follow up actions etc. C omputers also allow for greater flexibility in
recording the data while they are collected as well as greater ease during
the analysis of these data. In research studies, the preparation and
inputting data is the most labor intensive and time consuming asp ect of
the work. Typically, the data will be initially recorded on a questionnaire
or record form suitable for its acceptance by the computer. To do this the
researcher in conjunction with the statistician and the programmer, will
convert the data into Mic rosoft word file or excel spreadsheet. These
spreadsheets can be directly opened with statistical software for analysis.
D. ROLE OF COMPUTERS IN DATA ANALYSIS:
This phase consists of statistical analysis of the data and
interpretation of results. Many s oftware are now available to perform the
‘mathematical part of the research process i.e. the calculations using
various statistical methods. The software like SPSS, Stata, JMP, SAS etc
are freely available to analyse the data for different statistical tech niques.
E. ROLE OF COMPUTERS IN RESEARCH DISSEMINATION:
This phase is the publication of the research study. It helps the
researcher to compile the data and put it into one format and book so that a
complete thesis can be formed. The research article is typed in word
format and converted top or table data format (PDF) and stored and/or
published in the World Wide Web.
To conclude, computers are useful tools that make the research
process easier and faster with accuracy and greater reliability and fewer
errors. The programmer or the computer operator should have a thorough
knowledge about the abilities and limitations of the software used for
better use of computers.
8.3 ETHICAL NORMS IN RESEARCH:
8.3.1 MEANING
The term research ethics refers to a wide variety of values, norms,
and institutional arrangements that help constitute and regulate scientific
activities. Research ethics is a codification of scientific morality in
practice.
Ethics are the moral principles that a person must follow,
irrespectiv e of the place or time. Behaving ethically involves doing the
right thing at the right time. Research ethics focus on the moral principlesmunotes.in
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120that researchers m ust follow in their respective fields of research. The
researcher should not undertake research misconduct such as:
Fabrication making up data or results and recording or reporting
them.
Falsification manipulating research materials, or changing or
omitting data or results such that the research is not accurately
represented in the research record.
Plagiarism the appropriation of another person's ideas, processes,
results, or words without giving appropriate credit.
Research ethics provides guidelines for the responsible conduct of
research. In addition, it educates and monitors researcher / scholars
conducting research to ensure a high ethical standard. The following is
ageneral summary of some ethical principles:
1)Honesty: The researcher should hones tly report data, results, methods
and procedures, and publication status. He/she should not fabricate,
falsify, or misrepresent data.
2)Objectivity: The researcher should strive to avoid bias in
experimental design, data analysis, data interpretation grant writing,
expert testimony, and other aspects of research.
3)Carefulness: The researcher should avoid careless errors and
negligence. He/she should ca refully and critically examine the work.
He/she should keep good records of research activities.
4)Openness: The researcher should share data, results, ideas, tools,
resources. Wherever, required references must be mentioned to give
credit to the original w ork of the researcher. He/she should be open to
criticism and new ideas.
5)Respect for Intellectual Property: The researcher should honour
patents, copyrights, and other forms of intellectual property. He/she
should not use unpublished data, methods, or resu lts without
permission. Researcher should give credit to the other author if his
content is used and should not plagiarize.
6)Confidentiality: The researcher should maintain the confidentiality
about the identity of respondent who respond to the research by filling
up questionnaire or giving interview. As well as other records which
are to be kept secret should not be disclosed to any other person.
7)Responsible Publication: The researcher should publish in order to
advance research and scholarship, not to adv ance just your own career.
He/she should avoid wasteful and duplicative publication.
8)Respect for Colleagues: The researcher should respect his/her
colleagues and treat them fairly. It is necessary to maintain their
motivation in carrying on research activ ity.munotes.in
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1219)Social Responsibility: The research should strive to promote social
good and prevent or mitigate social harms through research. The
research should contribute to the welfare of the society.
10)Norms and values of research: Research is a systematic and so cially
organised activity governed by various specific and values. In the
humanities and social sciences, involvement and interpretation are
often integral parts of the research process. Different academic
approaches and theoretical positions may also allo w for different, but
nonetheless reasonable, interpretations of the same material.
11)Respect for third parties : Researchers should consider and anticipate
effects on third parties that are not directly included in the research.
Researchers should take accoun t of the possible negative consequences
for third parties. This is particularly important when vulnerable
individuals, like children and minors, are indirectly involved in the
research.
8.4 PLAGIARISM IN RESEARCH:
8.4.1 DEFINITION
According to Oxford Di ctionary of English, plagiarism is "the
practice of taking someone else's work or ideas and passing them off as
one's own." Plagiarism is presenting someone else’s work or ideas as your
own, with or without their consent, by incorporating it into your work
without full acknowledgement. All published and unpublished material,
whether in manuscript, printed or electronic form, is covered under this
definition. Plagiarism may be intentional or reckless, or unintentional.
8.4.2 TYPES OF PLAGIARISM
Source: ht tps://www.scribbr.com/plagiarism/types ofplagiarism/
1.Global Plagiarism: It means copying entire work of someone and
quoting as if you’re your work. E.g.: If you get someone else to writemunotes.in
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122an essay or assignment for you, or if you find a text online and su bmit
it as your own work, you are committing plagiarism. Because it
involves deliberately and directly lying about the authorship of a work,
this is one of the most serious types of plagiarism, and it can have
severe consequences.
2.Paraphrasing Plagiarism: Paraphrasing means rephrasing a piece of
text in your own words. Paraphrasing without citation is the most
common type of plagiarism.
Paraphrasing itself is not plagiarism so long as you properly cite your
sources. However, paraphrasing becomes plagiarism when you read a
source and then rewrite its key points as if they were your own ideas.
Additionally, if you translate a piece of text from another language,
you need correctly cite the original source. A translation without a
source is still plagiarism, as the idea is of someone else.
3.Verbatim Plagiarism: Verbatim plagiarism when you directly copy
text from a source and paste it into your own document without
acknowledging the creator. If the structure and the majority of the
words are the same as in the o riginal, then it is verbatim plagiarism,
even if you delete or change a couple of words here and there.If you
want to use an author’s exact words, you need to quote the original
source by putting the copied text in quotation marks and including an
intextcitation.
4.Mosaic Plagiarism: Mosaic plagiarism means copying phrases,
passages and ideas from different sources and putting them together to
create a new text. This includes slightly rephrasing passages while
keeping many of the same words and structure as the original. This
type of plagiarism requires a little more effort and is more insidious
than just copying and pasting from a source, but plagiarism checkers
like Turnitin can still easily detect it.
5.Self Plagiarism: Selfplagiarism means reusing work th at you’ve
previously submitted. Even though it’s your own work, it’s considered
dishonest to present a paper or a piece of data as brand new when
you’ve already gotten credit for the work.
There are a couple of different versions of self plagiarism. The mo re
serious is to turn in a paper you already submitted for a grade to
another class. Unless you have explicit permission to do so, this is
always considered self plagiarism.Self plagiarism can also occur when
you use ideas, phrases or data from your previo us assignments. As
with paraphrasing, reworking old ideas and passages is not inherently
plagiarism, but you should cite your previous work to make the origins
clear.
6.Incorrect citation: The key to avoiding plagiarism is citing your
sources. You need to co rrectly format your citations according to themunotes.in
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123rules of the citation style you are following. If you don’t include all the
necessary information or you put it in the wrong place, you could be
committing plagiarism. Most styles require in text citations plu sa
reference list or bibliography at the end of your paper, where you give
full details of every source you cited.
To avoid plagiarism, researcher must give credit whenever he/she:
Directly quote another person's written or spoken words. Be sure to
enclo se these words and/or sentences in quotations marks!
Paraphrase another person's spoken or written words. Paraphrase
means to re write in your own words; merely reordering or substituting
words is still considered plagiarism!
Use theories, ideas, opinions, research, etc. that are not your own.
Use historical, statistical, or scientific facts or data that are not your
own.
8.5 SUMMARY
The methodology has changed drastically over a period of time and
thus this unit consists of modern techniques adopted to m ake a
research project more genuine and useful for readers. Thus a detailed
explanation of Plagiarism has been given. Different types of
Plagiarism are highlighted and dos and don'ts to avoid Plagiarism have
also been mentioned. The roles of computers have increased at every
level while conducting research and the same has been explained in
detail. Different software can be used to analyse the data, create charts
and also to manage the data in proper sequence. Every researcher
needs to follow certain ethics while conducting research so that
research is genuine and concrete. Thus, ethical norms in research have
also been captured in the unit.
8.6 EXERCISE
Practice questions:
1.Explain the role of computers in research.
2.What are ethics followed in research.
3.Write a note on Plagiarism
4.Describe different types of Plagiarism
Fill in the blanks
1._______________refers to a wide variety of values, norms, and
institutional arrangements that help constitute and regulate scientific
activities.
2._____________________ manipulating research materials, or
changing or omitting data or results.munotes.in
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1243.SPSS software helps to __________ the research data.
4.__________________ is the practice of taking someone else's work
or ideas and passing them off as one's own.
Answers: 1. Ethics 2 . Falsification 3.Analyse 4. Plagiarism
True or False:
1.Plagiarism check is not at all important –False
2.SPSS software can be used for analysis of the data –True
3.Usage of Ms Power Point can help the researcher to sort, analyse
and present the data as per requirement. False
4.Usage of computer has made the job of researcher very easy. –
True
8.7 REFERENCES:
1. C. R. Kothari. Research Methodology: Methods & techniques. 2nded.
2. P.S.S. Sunder Rao, J. Richard.Introduction to Biostatistics and Res earch
Methodology. 4thed.
https://labwrite.ncsu.edu/res/res citsandrefs.html
https://www.slideshare.net/s aravananmsw/role ofcomputers in
research
https://www.forskningsetikk .no/en/guidelines/social sciences 
humanities lawandtheology/guidelines forresearch ethics inthe
social sciences humanities lawandtheology/
https://www.scribbr.com/plagiarism/types ofplagiarism/
munotes.in