QUA 609: Applied Multivariate Analysis

Outline of Course Content:
 

Content

Introduction to Multivariate Analysis.

Planning Data Analysis. Application of SPSS Software. 

Multiple Regression Analysis. Applications of SPSS software.

Assignment 1   (2.5 points)

Reliability Analysis. Application of SPSS Software. 

 Assignment 2   (2.5 points)

Factor Analysis. Application of SPSS Software. 

Assignment 3   (2.5 points)

Midterm Exam(30 points)

Principal Component Analysis.  Application of SPSS   Software.    

Cluster Analysis. Application of SPSS   Software.    

Discriminant Analysis. Application of SPSS   Software.    

Assignment 4   (2.5 points)

Conjoint Analysis. Applications of SPSS software.

MANOVA and Canonical Correlation. Applications of SPSS software.

Project (20 points)

Final Exam (40 points)

 
 
Books Recommended:
 
1. Applied Multivariate Statistical Analysis, 6/E by Richard A. Johnson and Dean W. Wichern. Prentice Hall.
http://www.udel.edu/oiss/pdf/617.pdf
2. Practical Multivariate Analysis, 5/E by Abdelmonem Afifi, Susanne May and Virginaia A. Clark. CRC Press.
3. Methods of Multivariate Analysis, 3/E by Alvin C. Rencher and William F. Christensen. Wiley.
4. Business Research Methods, by Nandagopal R, Arul Rajan K and Vivek N. Excel Books.
5. Marketing Research – Text and Cases, by Nargundkar R. McGraw Hill.
6. SPSS for Windows – Analysis without Anguish, by Sheridan J Coakes, Lyndall Steed and Peta Dzidic. Wiley.
7. IBM SPSS for Intermediate Statistics, 5/E by Nancy L.Leech, Karen C.Barrett and George A. Morgan. Routledge (Taylor & Francis Group).
8. IBM SPSS 19 Statistics Made simple, by Colin D. Gray and Paul R. Kinner. Psychology Press (Taylor & Francis Group)
 
 
 
 
 
Project for QUA 609
Research Paper
 
The aim of this project is to go through a real analysis and use the statistical methods taught in this course to come up with a research paper including some objective findings. The final output should be written in an academic form where the grading will be done according to the following:
 

• Abstract                                                                     10%
• Introduction & Literature review                            10%
• Materials & Methods                                                20%
• Analytical part                                                           35%
• Interpretation                                                            25%

 
Conditions:
 
1:         Find a multivariate data set.
2:         Upon your data structure define, theoretically, the following:

• The problem
• Goals
• Study Design
• Study Questions
• Study Questionnaire

2:         Provide some literature review on your problem using at least 3 academic papers.
3:         The descriptive part of your paper should contain:

• Frequency distributions of variables.
• Graphics and tables
• Sample statistics (Mean, Mode, Variance … etc.).

4:         Construct multivariate analysis which includes one or more of the following:

• Reliability Analysis
• Simple and Multiple regression
• Factor analysis
• Principal Component Analysis
• Discriminant analysis
• Cluster analysis
• Conjoint analysis

5:         Write a research paper on your work.
6:         Hand in the final paper by 10th May 2017.
7:         Check your final paper for spelling and grammar before submitting.