Description: Computationally intensive statistical methods. Topics include statistical learning (cross-validation, GAMs, classification and regression trees), nonparametric methods (bootstrapping and permutation tests) as well as general-purpose algorithms (MCMC). Emphasis placed on both underlying statistical concepts and implementing resulting algorithms in a high-level mathematical programming language on non-tidy data. Co-convened with STA 578. Letter grade only.
No sections currently offered.
Prerequisite: (STA 471 with a grade of C or better) and STA 445