Applied Multivariate Data Analysis

Catalog description

This course examines the principles behind statistical data analysis for multivariate data, and introduces the students to major areas of multivariate I data analysis. Topics include multiple and logistic regression, principal component analysis, factor analysis, cluster analysis, MANOVA, multidimensional scaling, discriminant analysis and canonical correlation. The students will use at least one statistical software package. Previous exposure to linear algebra and univariate calculus, statistics, and probability are assumed..