Multivariate Statistical Analysis concerns methods of simultaneous analysis of multiple outcome variables. The course will introduce basic theory and applications for analyzing multi-dimensional data. Topics include principal component analysis, factor analysis model, canonical correlation, multi-dimensional scaling, discriminant analysis, clustering methods, and common techniques of dimension reduction. In addition to traditional multivariate statistical inferences and methods based on Gaussian models, new developments in high dimensional data analysis will be discussed. Theoretical derivations will be presented with emphasis on motivations, applications and hands-on data analysis.