STAT 4130
Applied Multivariate Statistics
Course Description
Pre-Requisite(s):
A prior course in mathematical statistics, a prior course in linear algebra, and a prior course in programming
This course develops fundamental methodology to the analysis of multivariate data using computational tools. Topics include multivariate normal distribution, multivariate linear model, principal components and factor analysis, discriminant analysis, clustering, and classification.
