ST 334 - Applied Multivariate Analysis

The course focuses on classic and new multivariate methods. In particular, the main subject areas are dimension reduction techniques (principal components analysis and correspondence analysis), classification, and clustering methods (multidimensional scaling, discriminant analysis, cluster analysis, and classification and regression trees), analysis of covariance structure, and latent variable models (factor analysis and canonical correlation analysis). Appropriate computer programs are used for analysis of real data sets. Examples and exercises are taken from a broad range of subject areas.
3 class hrs

Prerequisites & Notes
(Prerequisites: ST 331 and ST 332, or permission of instructor)

Credits: 3