Spring 2022

Generalized Linear Models and Mixed Models

Listed in: Mathematics and Statistics, as STAT-456

Moodle site: Course

Faculty

Brittney E. Bailey (Section 01)

Description

Linear regression and logistic regression are powerful tools for statistical analysis, but they are only a subset of a broader class of generalized linear models. This course will explore the theory behind and practical application of generalized linear models for responses that do not have a normal distribution, including counts, categories, and proportions. We will also delve into extensions of these models for dependent responses such as repeated measures over time.

Requisite: STAT 230 and STAT 360. Limited to 20 students. Spring semester. Professor Bailey. 

If Overenrolled: Priority for Statistics majors

Keywords

Quantitative Reasoning

Offerings

2022-23: Offered in Spring 2023
Other years: Offered in Spring 2021, Spring 2022