Data Analysis with R

Catalog description

Introduces techniques for exploring, analyzing, and visualizing data in R. Intended for students who already have some background in probability and statistics and/or 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 of even-numbered years only. Prerequisite: grade of C or better in MA 218 or MA 230.