Results for STATS 305C: Methods for Applied Statistics II: Applied Multivariate Statistics

Theory, computational aspects, and practice of a variety of important multivariate statistical tools for data analysis. Topics include classical multivariate Gaussian and undirected graphical models, graphical displays. PCA, SVD and generalizations including canonical correlation analysis, linear discriminant analysis, correspondence analysis, with focus on recent variants. Factor analysis and independent component analysis. Topic modeling. Multidimensional scaling and its variants (e.g. Isomap, spectral clustering). Matrix completion. Students will be expected to program - ideally in R. Prerequisites: Stats 305a and Stats 305b or equivalent. (NB: prior to 2016-17 the 305ABC series was numbered as 305, 306A and 306B).