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%)