Methods for Multivariate Data

3 credits · Undergraduate

This course discusses practical techniques for the analysis of multivariate data. Topics covered include estimation and hypothesis testing for multivariate means and variances; partial, multiple and canonical correlations; principal components analysis and factor analysis for data reduction; multivariate analysis of variance; discriminant analysis for classification; and cluster analysis. Prerequisite(s): One of MATH 150-3 or MATH 220-3, and one of MATH 471-3 or STAT 471-3 Preclusion(s): MATH 475-3, MATH 499-3 when offered as Applied Multivariate Analysis