MA 538 Data Analysis With R

Covers techniques for exploring, analyzing, and visualizing data in R. Intended for students who already have a background in probability and statistics and scientific computing. Topics include testing hypotheses, bootstrapping, Bayesian methods, and predictive analysis. Students will also learn strategies for dealing with missing or messy data and coping with large data sets. Offered fall semester, even-numbered years, only. Prerequisite: a grade of C or better in MA 523 and MA 528. (3)