Item No 414 Certificate Course in Data Analysis Using SPSS Software 1_1 Syllabus Mumbai University by munotes
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UNIVERSITY OF MUMBAI
Syllabus for the
Certificate Course in Data Analysis
Using SPSS Software
(Duration –Six Months)
(To be started from the academic year 2019 –2020)
From December 2019
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O. 6518 :- Certificate Course in Data Analysis using SPSS
Software .
The Course
Department of Statistics, University of Mumbai, Mumbai has specially designed certificate
course in Data Analysis using SPS S Software for those students who are pursuing their research
degree in social sciences, medical sciences, Biological sciences, Management sciences etc. and
industr y professionals. In this course the candidates shall undergo hands on training in SPSS
softw are. The course is of 60 hour s duration and c ourse will be taught on computer using SPSS
software. Course will be conducted two times in a year.
Focus
The main focus of the course will be on to solve their research question using SPSS software. As
you kno w that, students are facing problem specially w ho are pursuing research in their subject
that how to manage and analyze the data after collection of survey questionnaire . Course will
be focus on how to analyze survey questionnaire using SPSS software. Also students should
make aware to chose appropriate s tatistical technique and interpret results.
Faculty
This course will be taught by highly qualified experienced teachers and who are expert in
handling SPSS software’s from industries.
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O. 651 9 :- Eligibili ty
Any graduate from Mumbai University or any other recognized university.
Assessment
The course coordinator will be in charge of the examinations. One internal test of 40 marks will
be conducted after approximately 20 hours teaching . Course end e xaminati on wil l be
conducted on SPSS software of 60 marks .
The following grading scheme will be adopted to issue the certificate.
Marks in percentage Grade
70 and above A
65-69 B+
60-65 B
55-59 C+
50-54 C
45-49 D
0-45 Attendance Certificate
Certificates w ill be issued by the university on the performance record of the students.
R. 9263 :- Intake capacity
30 students . Minimum number of students to be admitted should be 12 in order to conduct the
course in that academic year. If more applications are receive d then admission will be based on
their interview performance.
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R. 926 4 :- Duration of Course
60 Hours duration . Course will be conducted on ce in a week either Saturday or Sunday
(10 am to 3pm) .
R. 926 5 :- Fee Structure of the course is as under
Head Amount in Rupees
Information brochure and application form fee 200.00
Tuition fee 10000.00
Examination fee 500.00
Certificate 100.00
Total 10800.00
Remuneration to faculty:
Rs.1200/- per clock hour
Required Non Teaching Staff:
Office assistant and peon is available in department for PGDASS course. Additional lump sum
amount of Rs. 6000/ - to be given to office assistant and 3000 to the peon after completion of
the course.
Following required infrastructure is available in Department:
1) Computer lab with good internet facility .
2) SPSS software is available in department.
3) Printers, LCD projector, White board .
4) AC for computer laboratory.
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Detailed syllabus for the course.
Sr.no. Title Content of Syllabus
1 Introduction Type of Scale of Mea surements , Choosing appropriate scale
and measurement to the data , Preparing codebook.
Getting to Know SPSS: Starting SPSS, Working with data file,
SPSS windows, Menus, Dialogue boxes.
Preparing the Data file: Creating data fil e and entering data,
Definin g the variables, Entering data, modifying data file,
import file.
Screening and cleaning data, Manipulation of data.
2 Preliminary Analysis Descriptive statistics: Categorical variables, continuous
variables, checking normality, outliers checking.
Choosin g the right statistics: Overview of different
statistical techniques, Decision making process.
3 Statistical techniques :
Explore relationship
among variables Correlation: Pearson product moment correlation,
Spearman rank correlation, Partial correlation, Simple
linear regression,
Multiple Linear Regression: Assumptions, overall
significance, multicollinearity, Variable selection methods.
4 Statistical techniques:
Compare means One sample and two Independent sample t test, Paired
sample t test, One way A nalysis of variance, Two way
ANOVA, Multivariate ANOVA, Analysis of Covariance ,
Repeated measures .
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5 Non -Parametric
statistics Independent Chi square Test, Mann - Whitney test ,
Wilcoxon signed rank test, Kruskal - Wallis test.
6 Advanced Mod els:
Multivar iate statistical
techniques. Logistic Regression and Discriminant Analysis, Factor
Analysis, Cluster Analysis.