Prerequisite: ILRST 3120 , STSCI 2200, or equivalent; some knowledge of matrix-based regression analysis.
Theory and application of classical and modern multivariate methods to data arising in biology, sociology, economics, engineering and other fields. Topics include MANOVA, principal components, factor analysis, structural equations, discriminant analysis and clustering.
Outcome 1: Students will be able to explain the utility of multivariate methods for MANOVA, PCA, factor analysis, discriminant analysis and clustering.
Outcome 2: Students will be able to analyze multivariate data using modern statistical software.