Multivariate Statistical Methods, Advanced

Instructor(s): Douglas Steinley

A very strong background in statistics at least at the level of the ICPSR courses Regression Analysis II: Linear Models and Mathematics for Social Scientists II is necessary for this course. The purpose of this workshop is to discuss linear models that are useful for analyzing multivariate data. After briefly reviewing univariate linear models, the course will cover multivariate hypothesis testing, principal components analysis, discriminant analysis, canonical correlation analysis, cluster analysis, and factor analysis. The level and breadth of coverage is roughly equivalent to that found in the following multivariate texts: Cooley and Lohnes, Multivariate Data Analysis; Tatzuoka, Multivariate Analysis; and Johnson and Wichern, Applied Multivariate Statistical Analysis.