Regression Theory and Applications

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 MATH 0311) 3 hrs lect./disc.

Schedule
1:45pm-2:35pm on Monday, Wednesday, Friday (Feb 14, 2022 to May 16, 2022)
Location
Munroe Hall 317
Instructors