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

Example Syllabus