This course covers computational statistical concepts for analyzing large data sets including. Topics include: maximum likelihood, generating random variables, estimating distributions via simulation, expectation maximization, data partitioning including bootstrapping, jackknifing and cross- validation, multivariate, parametric and non-parametric regression, principle components, classification and regression trees, and multivarite analysis of variance (MANOVA). Statistical packages such as MATLAB will be utilized to implement the concepts learned in the course. Prerequisites: None. (F;S)