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Data Analysis For Social Science Teachers

By Prof B. Raja Shekhar   |   HRDC University of Hyderabad
Statistical analysis is playing a major role in social science research. In the present era the top tier journal editors are expecting the researchers to use scientific approach to analyse the data collected through primary or secondary sources. This course will help the social science researchers and teachers to understand the process of analysing the data and reporting the results in their research projects using different software's.

Learning Objectives:
1. To classify the construct measurement process in social science research.
2. To demonstrate the Univariate, Bivariate and Multivariate data analysis techniques.
3. To perform the data analysis using various software packages (MS Excel, IBM SPSS and AMOS).
4. To learn the process of reporting the results.

Intended Audience: Research Scholars and faculty members from social sciences. 
Prerequisite: Nil. However prior knowledge on basic statistics and research methodology is an added advantage. 

Resource Persons:

1. Prof. B. Raja Shekhar, University of Hyderabad, Hyderabad.

2. Prof. G.V.R.K Acharyulu, University of Hyderabad, Hyderabad.

3. Prof. Jayanth Jacob, Anna University, Chennai.

4. Dr. Irala Lokananda Reddy, University of Hyderabad, Hyderabad.

5. Dr. D.V.Srinivas Kumar, University of Hyderabad, Hyderabad.

6. Dr. Pramod Kumar Mishra, University of Hyderabad, Hyderabad.

7. Dr. R. Mahesh, Institute of Management Technology, Hyderabad.

8. Dr. P. Murugan, University of Hyderabad, Hyderabad.


Learners enrolled: 5853

SUMMARY

Course Status : Completed
Course Type : Core
Duration : 16 weeks
Start Date : 01 Oct 2019
End Date : 20 Jan 2020
Exam Date :
Enrollment Ends : 02 Nov 2019
Category :
  • Annual Refresher Programme in Teaching (ARPIT)
  • Level : Continuing Education
    This is an AICTE approved FDP course

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    COURSE LAYOUT


    Week 1
    Introduction to Data Analysis
    What is data? Types of Measurement
    Reliability and validity

    Week 2
    Measures of central tendency and dispersion
    Different types of distributions
    Selection of appropriate data analysis technique

    Week 3
    Inferential statistics I
    Inferential statistics II

    Week 4
    Introduction to SPSS
    T-test and one-way ANOVA and ANCOVA using SPSS (Theory and Practical)

    Week 5
    Correlation and simple Regression using SPSS
    Introduction to multivariate data analysis

    Week 6
    Multiple regression analysis
    Multiple regression analysis using SPSS

    Week 7
    Logistic regression
    Logistic regression using SPSS

    Week 8
    Multivariate analysis of variance 
    Multivariate analysis of variance using SPSS
    Conjoint analysis
    Conjoint analysis using EXCEL

    Week 9
    Exploratory factor analysis 
    Exploratory factor analysis using SPSS
    Cluster analysis
    Cluster analysis using SPSS

    Week 10
    Multi-Dimensional Scaling 
    Multi-Dimensional Scaling using SPSS
    Forecasting Methods 

    Week 11
    Structural Equation modelling (SEM)
    Confirmatory factor analysis (CFA)

    Week 12
    CFA using AMOS
    SEM using AMOS

    Week 13
    Common method bias issue in survey research
    Common Method bias using unmeasured method factor using AMOS

    Week 14
    Mediation analysis
    Mediation analysis using regression and PROCESS Macro

    Week 15
    Moderation analysis
    Moderation analysis using regression and PROCESS Macro

    Week 16
    Moderated mediated analysis
    Moderated Mediation analysis using PROCESS Macro
    Reporting guidelines

    BOOKS AND REFERENCES

    1. Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2013). Multivariate data analysis, 7/e. Pearson India.
    2. Hayes, A. F. (2017). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. 2nd edition, Guilford Press.
    3. Malhotra, N. K., & Birks, D. F. (2012). Marketing research: An applied approach. Pearson Education.6th edition. 
    4. Zikmund, W. G., Babin, B. J., Carr, J. C., & Griffin, M. (2013). Business research methods. Cengage Learning.
    5. Levin, R. I. (2011). Statistics for management. Pearson Education India.

    INSTRUCTOR BIO


    Prof. B. Raja Shekhar
    has a commendable track record in the field of higher education as an academician and academic administrator. He has completed two doctorates in Management and Psychology. Prof. Shekhar participated in a three and half month Faculty Development Programme at Indian Institute of Management, Ahmadabad. He has guided 15 Ph.D. scholars successfully and currently guiding 8 more research scholars. Prof. Shekhar also coordinating a MOOCs in Research Methodology for Social Sciences through SWAYAM of MHRD. He has been appointed as one of the members of the expert committee constituted by UGC to draft Learning Outcomes Based Curriculum Framework for Management. He has published about 76 research papers in reputed International, National Journals and conference proceedings. Prof. Shekhar is a specialist in the area of scale development in Service Quality and has been doing extensive research in various issues of service quality and developed scales in measuring higher education service quality (HiEduQual) and railway service quality (RailQual). Prof. Shekhar has been delivering lectures in several workshops/FDPs on research methodology across the country. His primary areas of interests include Service Quality, Quantitative Techniques, Operations Management, Research Methodology and Industrial & Organizational Psychology. To know more about his work visit: www.profbrajashekhar.in.

    COURSE CERTIFICATE



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