Introduction to Multivariate Statistics

Catalog description

This course introduces students to the concepts and methods used to analyze multivariate data in an applied context. Topics include exploring and visualizing multivariate data, linear algebra for multivariate methods, principal components and factor analysis, canonical correlation, discriminant and cluster analysis, multivariate normal distributions, MANOVA, and other dimensionality reduction techniques. Emphasis will be placed on interpreting results and applying methods using real-world data. Statistical software such as R will be used for computation and visualization.