Research Methodology II- Practical

Paper Code: 
24DATG802
Credits: 
02
Contact Hours: 
30.00
Max. Marks: 
100.00
Objective: 

This course will enable the students to collect and analyze data analysis using software applications, interpretation and reporting of results. 

 

 

 

 

 

 

 

 

 

 

 

 

Course Outcomes: 

 

Course

Learning outcome

(at course level)

Learning and teaching strategies

Assessment Strategies

Course Code

Course

Title

 

24DATG802

 

 

Research Methodology II – Practical

(Practical)

CO229: Examine the basic concept of common parametric and non-parametric tests.

CO230: Organize and appraise the  results produced by statistical software

CO231: Examine and appraise different non parametric tests.

CO232: Appraise simple regressions and multivariate analysis.

CO233: Organize and evaluate various techniques of advanced analysis for research work.

CO234: Contribute effectively in course-specific interaction

Approach

in

teaching:

Interactive

Lectures,

Discussion,

Tutorials,

Problem solving sessions, Presentations

Learning

activities

for the

students:

Self-learning

assignments, Case Study analysis, Presentations, Group discussions

  

Continuous Assessment Test, Semester End Examinations, Quiz, Solving numerical problems, Assignments, Class Presentations, Individual and group projects.

 

6.00
Unit I: 
Statistical Testing
  • Statistical Testing: Parametric vs. Non parametric.
  • Parametric Tests- t-test: One Sample, Independent Sample, Paired t test.

 

6.00
Unit II: 
Analysis of variance
  • Assumptions of One Way ANOVA, Testing for differences in mean between the group, Measure of Association, Assumption of Two way ANOVA, Procedure for Testing Two Way ANOVA.

 

6.00
Unit III: 
Non Parametric Tests
  • Non Parametric Tests: Mann Whitney U test, Wilcoxon Signed ranks test, Kruskal Wallis Test, Friedman Test.
  • Chi square Test: Test of Independence, 2x2 Cross tabulation, Layered cross tab, Goodness of fit.

 

6.00
Unit IV: 
Regression

                                                                        

  • Assumptions, Linear Regression, Multiple Regression

 

 

6.00
Unit V: 
Advanced Analysis
  • Factor Analysis, Principal Component Method, Confirmatory Factor Analysis.

 

Unit V: Advanced Analysis:                                                                                       (6 Hours)

 

  • Factor Analysis, Principal Component Method, Confirmatory Factor Analysis.

 

Essential Readings: 
  • Andy Field, Discovering Statistics Using IBM SPSS Statistics,Sage Publications
  • Kiran Pandya, Smruti Bulsari, Sanjay Sinha, SPSS in Simple Steps, Dreamtech Press
  • A. Rajathi & P. Chandran (2012), SPSS for You, MJP publishers.
  • Lawrence M Mayers, Glenn C Gamst, A J Guarind, Performing Data Analysis Using SPSS, Wiley

 

 

 

References: 

Suggested Readings:

 

  • S. Ajai Gaur (2009), Statistical methods for practice & research: A guide to Data Analysis using SPSS, Sage Publishers.
  • Seyed Reza Hashemian Rahaghi, Farnaz Abed Ashtiani, Basic of Statistics & SPSS, create space independent publishing platform.
  • Keith Mc Cormick, Jesus Salcedo, Jon Peck, Andrew Wheeler, SPSS Statistics for Data Analysis and Visualization, Wiley
  • James B Cunningham (2011), Using SPSS: An interactive hands- on Approach, Peacock publisher, 3rd Edition.

 

E-Content:

 

Reference Journals:

  • Business Perspectives and Research
  • FIIB Business Review
  • Harvard Business Review
  • IUP Journal of Accounting Research
  • Jindal Journal of Business Research
  • Nirma University Journal of Business & Management Studies
  • Oorja
  • The Chartered Accountant
  • The ICFAI reader
  • The Indian Journal of Commerce
  • Vikalpa: Journal for Decision Makers
Academic Year: 
2024-2025
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