SDE562-Applied Multivariate Methods

 
SDE 562: Applied Multivariate Methods
 
Outline of Course Content:
 

Content

Introduction to Multivariate Analysis.

Planning Data Analysis. Application of SPSS Software. 

Reliability Analysis. Application of SPSS Software. 

 Assignment 1   

Factor Analysis. Application of SPSS Software. 

Assignment 2  

Principal Component Analysis.  Application of SPSS   Software.    

Assignment 3  

Midterm Exam(30 points)

Cluster Analysis. Application of SPSS   Software.    

Assignment 4  

Discriminant Analysis. Application of SPSS   Software.    

Conjoint Analysis. Applications of SPSS software.

MANOVA and Canonical Correlation. Applications of SPSS software.

Project (30 points)

Final Exam (40 points)

 
 
Books Recommended:
 
1. Applied Multivariate Statistical Analysis, 6/E by Richard A. Johnson and Dean W. Wichern. Prentice Hall
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 SDE562
 
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 some objective findings. The final output should be written in an academic form where the grading will be done according to the following:
 

• Study design and goals                     10%
• Literature review                              10%
• Descriptive statistics part                  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
• MANOVA
• Canonical Correlation

5:         Write a research paper on your work.
6:         Hand in the final paper by the end of week 14.
7:         Check your final paper for spelling and grammar before submitting.