This course presents classical and modern approaches for analyzing multivariate and high dimensional data, including principal components, factor analysis, discriminant analysis, clustering, new developments on dimension reduction, large-scale covariance matrix estimation and multiple testing. All of these approaches will be covered in the context of Marketing, Finance and other important business decisions. Computational issues for both traditional and new methodologies will also be discussed.