STAT 6130
Applied Multivariate Statistics
Course Description
Pre-Requisite(s):
Graduate standing in Statistics, or instructor permission
This course develops fundamental methodology to the analysis of multivariate data. Topics include the multivariate normal distributions, multivariate regression, multivariate analysis of variance (MANOVA), principal components analysis, factor analysis, and discriminant analysis. Conceptual discussion in lectures is supplemented with hands-on practice in applied data-analysis tasks using SAS or R statistical software.
