Instructor: Raquel Prado, BE 365C 

Course Description

This course presents tools for exploratory data analysis (EDA) and statistical modeling in R. Topics include: numerical and graphical methods for EDA, linear and logistic regression, ANOVA, PCA, and tools for acquiring and storing large data. No R knowledge is required. Enrollment is restricted to graduate students. 

Classroom, Lecture Time & Office Hours

Lectures: Mon, Wed 5:20-6:55pm in Kresge Clrm 319 

Office Hours (Tentative): Tu 2:30-3:30pm and Th 11:30am-12:30pm in BE-365C

Textbook and other recommended books 

R by Example (2012) by Jim Albert and Maria Rizzo, Springer Use R! Series

Other recommended books:

Modern Applied Statistics with S (2002, Fourth Edition) by W.N. Venables and B.D. Ripley, Springer. 

R for Data Science (2017) by Garrett Grolemund and Hadley Wickham 

ggplot2 (2016) by Hadley Wickham, Springer Use R! Series

Course evaluation: Homework Assignments (35%); Exam (35%); Final Project (30%)