Multivariate Statistical Methods

Catalog description

The course emphasizes both the theoretical foundations and applied aspects of multivariate analysis. Students will examine data exploration, inference, and model-based approaches, including principal components, factor and canonical correlation analysis, discriminant and cluster analysis, MANOVA, and modern dimensionality reduction techniques. The course will also introduce extensions of these methods and encourage critical evaluation of their assumptions and limitations. Statistical software, such as R, will be used for implementation and analysis.