Basics of statistical learning, cross-validation, penalized least squares, principal component analysis, classification algorithms, decision trees, and clustering algorithms. Extensive use of a computer statistical package.
Prerequisites & Notes: MATH 342 Credits: 4 Grade Mode: Letter