multivariate data analysis - sta535
Course Objectives
Students will be expected to show competency regarding the following areas of study:
- Matrix Algebra and using PROC IML
- The Multivariate Normal Distribution
- Using MANOVA
- Principal Component Analysis
- Factor Analysis
- Classification Techniques
Course Topics
Multivariate data typically consist of many records, each with readings on two or
more variables,
with or without an "outcome" variable of interest. Procedures covered in this course
include
multivariate analysis of variance (MANOVA), principal component analysis, factor analysis
and
classification techniques. This course will require that students are comfortable
with matrix
algebra.
Example Syllabus