MTH-345 Statistical Methods II with R

Prerequisite: MTH-160 and MTH-245
Statistical Methods II with R is a second course in data analysis that focuses on modeling and prediction through the use of modern statistical learning techniques in Cran R. Topics include shrinkage methods (ridge regression and LASSO), bootstrapping, cross-validation, count regression, logistic regression, regression and classification trees (bagging, random forests, boosting), k-nearest neighbors, discriminant analysis, naive Bayes, support vector machines, principal components analysis, and clustering. Applications will be taken from a number of disciplines, including biology, economics, and public health. Additional topics may include Markov chains, simulation, and Bayesian statistics. 4 credits