Statistics 521 - Multivariate Analysis (Spring 2004)

Instructor: Dr. Chris Williams              Office: Room 414 Brink Hall 

Phone: 885-2802 (direct) or 885-2929 (Division office) 

Meeting times: MWF 1:30-2:20 Admin 227 
Office Hours: MWF 2:30-3:20 or by appointment. 

Prerequisites: Stat 401 or equivalent coursework. 

Text: Applied Multivariate Methods for Data Analysts 
by Dallas E. Johnson, Kansas State University 



The webpage will contain announcements, summaries of lectures,
lists of assignments with due dates, and other information.

Objectives: Multivariate analysis is concerned with analysis of data consisting of 
several measurements on each observation.  We will cover a number of ways to 
analyze such data, some of which are exploratory in nature, while others are used 
in confirmatory analyses. The course objective is for you to develop an 
understanding of the various methods of multivariate analysis and the ability to 
apply appropriate multivariate methods to your own research data.

Course Outline: 

1. Introduction to multivariate data and SAS. 
2. Sample correlations. 
3. Visualizing multivariate data, SAS Proc INSIGHT. 
4. Eigenvalues and eigenvectors.
5. Principal components analysis. 
6. Factor analysis. 
7. Discriminant analysis. 
8. Logistic regression methods. 
9. Cluster analysis. 
10. Mean vectors and covariance matrices. 
11. Multivariate analysis of variance. 
12. Prediction models and multivariate regression. 

We will use the SAS computer package throughout the course.


Homework: 20%
Test 1 25%
Test 2 25%
Project 10%
Final 20% Wednesday, May 12 at 1pm