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Applied Statistics III

  • Not Offered

3 units

Letter or Credit/No Credit

Methods for multivariate responses. Theory, computation and practice for multivariate statistical tools. Multivariate Gaussian and undirected graphical models, graphical displays. Hotelling's T-squared, principal components, canonical correlations, linear discriminant analysis, correspondence analysis, and recent variants of these. Hierarchical and k-means clustering. Bi-clustering. Factor analysis and independent component analysis. Topic modeling. Multidimensional scaling and variants (e.g., Isomap, spectral clustering, t-SNE). Matrix completion. Extensive work with data involving programming, ideally in R. Prerequisites: Stats 305A and Stats 305B or consent of the instructor.

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