Regression Theory and Applications (formerly MATH 0211)

Regression is a popular statistical technique for making predictions and for modeling relationships between variables. In this course we will discuss the theory and practical applications of linear, log-linear, and logistic regression models. Topics include least squares estimation, coding for categorical predictors, analysis of variance, and model diagnostics. We will apply these concepts to real datasets using R, a statistical programming language. (MATH 0200; and MATH 0116 or STAT 0116, or MATH 0311 or STAT 0311) 3 hrs lect./disc.

Schedule
9:45am-11:00am on Tuesday, Thursday (Sep 11, 2023 to Dec 11, 2023)
Location
Warner Hall 011
Instructors