FCHR5 Quantitative Research 2013-15

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TATA INSTITUTE OF SOCIAL SCIENCE, MUMBAI

School of Management and Labour Studies

Centre for Human Resources Management and Labour Relations

Name of the Programme M.A in Human Resource Management & Labour

Relations

Title of the Course FCHR5: Quantitative Research Methods

Course Instructors Prof. Gordhan K. Saini/ Prof. Bino Paul

Contact Details of Instructors Email: [email protected] Phone: 5802

Email:[email protected] Phone: 5804

Academic Session and

Semester

2013-15, 1st

Semester

Total Credits 2

Total Credit Hours 30

I. Brief Course Description

Quantitative Research Methods (QRM) course is designed to develop an understanding and

working knowledge of quantitative research techniques. The focus of this course is on thepractical use of quantitative techniques in a research problem.The course includes the study

of data management, descriptive statistics, inferential statistics and other multivariate data

analysis techniques.

II. Course Objectives

On completion of this course, students should be able to:

1. Understand data management - cleaning, coding, generating variables, handling largedataset, and apply in a research situation;

2. Understand sampling process and methods and develop survey instruments forcollecting primary data;

3. Understand and apply various descriptive and inferential statistics to analyse thecollected data;

4. Understand and apply appropriate multivariate statistical techniques in a researchproblem.

5. Apply quantitative research methods using statistics software program such as MS-EXCEL, PSPP, SPSS and interpret the results obtained from them.

III. Assessment

The student performance in the course will be evaluated as per the following assessment

scheme:

Assessment Scheme

Component Weight in %

A. Concurrent Evaluation(assignment) 60

B. End Term Examination 40

Assignment Submission Date: by the end of 14th

session

Note:

(i) Students who are not prepared with the readings or cases may be told to leave the class.

(ii) Session 5 to 15 will be handled by Prof. G. K. Saini


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SESSION WISE OUTLINE

Session 1: (Prof. Bino Paul)

Quantitative Research: Conceptualising the quantitative research studies- Designing a

quantitative research study, Thinking with Quantitative Data: Numbers versus Variables;

Testing ideas against data versus getting ideas from data; The factuality of data; Can data

prove everything? Types of data: primary data and secondary data; Do we have the right

data? Are they good data?

Levels of Measurements: Nominal, Ordinal, Interval and Ratio variables; Illustration through

examples; Knowing your data in a better way (cleaning & exploring): Recoding, merging,

generating new variables from the existing one, Case/Variable selection techniques, Outlier

identification

Session 2: (Prof. Bino Paul)

Univariate Measures: Tabular and Graphical Presentation- Descriptive statistics; Frequency

Distribution: Table- Preparation of a table and interpretation- Graphical presentation of Data -

Bar Diagram, Histogram, Frequency Polygon

Measures of Central Tendency and Dispersion: Mean, Median and Mode & variance,

coefficient of variation, range and quartile methods and interpretation

Session 3 & 4: (Prof. Bino Paul)

Bivariate Measures: Association between two variables being measured in same or different

scales (interval & nominal, nominal & nominal, interval & interval)

Sampling: Population and sample, cases and examples, probabilistic sampling, simple

random sampling, systematic sampling cluster sampling, stratified random sampling, single

stage and multi stage sampling. Sample size: Confidence level, error of margin and response

rate, sampling biases. Sample size calculation through demonstration

Development of Survey Instruments, Questionnaires, Schedules

Session 5

Normal distribution, Sampling distribution, Introduction to statistical inference, Statistical

estimation, Confidence intervals, T-distribution,

Session 6 & 7

Hypothesis Testing: T-test, One sample and two sample tests, Chi-square test

Reading

Martin, Leisa A. and Fraser, Scott L. (2002). Customer Service Orientation inManagerial and Non-Managerial Employees: An Exploratory Study, Journal of Business

and Psychology, 16(3): 477-484.

Session 8

Analysis of Variance (ANOVA), F-test

Reading


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Hossain, M.M. (2000). Job Satisfaction of Commercial Bank Employees in Bangladesh:A Comparative Study of Private and Public Sectors,Indian Journal of Industrial

Relations, Vol. 35 (3) pp. 347-361

Session 9

Association between continuous variables; Correlation, Regression

Readings

Note (1&2) on Correlation and Regression using SPSS Ramaswamy, K., Veliyath, R. and Gomes L. (2000). A Study of the Determinants of

CEO Compensation in India,Management International Review, 40(2): 167-191.

Session 10 & 11

Introduction to multivariate analysis: Multiple regression

Readings

Note on Multiple Regression using SPSS Koh, H. C. and Boo, E. H. Y. (2001). The Link between Organizational Ethics and

Job Satisfaction: A Study of Managers in Singapore. Journal of Business Ethics, 29(4): 309-324.

C. Balaji. (1988). Organizational Commitment of Job Satisfaction: Which ExplainsIntent to Quit Better.Indian Journal of Industrial Relations, Vol. 23 (3) pp. 313-328

Session 12

Factor Analysis (Principle Component Method)

Readings

Note on Factor Analysis using SPSS Chand, M. (2010). Human Resource Management Practices in Indian Hospitality

Enterprises: An Empirical Analysis,Managing Leisure, 15: 4-16 Rao, S. G. V. and Ganapathi, V. R, (1973). A Study of Factors Contributing to

Satisfaction and Importance of Industrial Personnel: A Test of the Two-Factor Theory.

Indian Journal of Industrial Relations, 9 (2): 233-262

Session 13

Logistics Regression

Session 14

Presentation of research results; Preparing result tables based on the analysis output

Introduction to index numbers: concepts and uses

Session 15

Concluding session: presentations, etc.

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Suggested Readings

Allan Bryman (2008), Social Research Methods, Oxford University Press, Newyork


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M N Murthy (1967), Sampling Theory Methods, , Statistical Pub. Society, - Series inprobability and statistics, Calcutta

Nachmias and Nachmias (2000): Research Methods in Social Sciences, WorthPublishers

Richard I. Levin and David S. Rubin (latest edition): Statistics for Management, PearsonEducation.

Hair, Black, Babin, Anderson and Tatham (latest edition) Multivariate Data Analysis,Pearson Education, 6/e.

S. Christian Albright, Wayne L. Winston, Christopher Zappe (latest edition) DataAnalysis and Decision Making With Microsoft Excel, Thomson Books/Cole.

Documents

FCHR5 Quantitative Research 2013-15