Generalized Linear Models (456-0-20)

Instructors

Noelle Samia
847.491.5772
2006 Sheridan Road

Meeting Info

Annenberg Hall G01: Tues, Thurs 11:00AM - 12:20PM

Overview of class

This course will focus on the theory and application of linear and generalized linear models and related statistical topics. Generalized linear models are a very broad family of statistical models, loosely described as follows. The response variable has a distribution in an exponential dispersion family and the mean response is related to covariates through a link function and a linear predictor. Generalized linear models allow a unified theory for many of the models used in statistical practice, including normal theory regression and ANOVA models, loglinear models, logit and probit models for binary data and models for gamma responses and survival data.

Registration Requirements

Regression Analysis, Introduction to Statistical Theory and Methodology

Evaluation Method

Homework/Projects

Class Materials (Required)

An Introduction to Generalized Linear Models, by Annette J. Dobson & Adrian G. Barnett, 3rd edition, Chapman & Hall/CRC; ISBN: 978-1584889502

As of April 2026, the Amazon price is $16.44 for paperback.

Class Materials (Suggested)

Foundations of Linear and Generalized Linear Models, by Alan Agresti, Wiley; ISBN: 978-1118730034 Generalized, Linear, and Mixed Models, by McCulloch, Searle, & Neuhaus, 2nd edition, Wiley; ISBN: 978-0470073711 Generalized Linear Models, by P. McCullagh & Nelder

Enrollment Requirements

Enrollment Requirements: REASON: Pre-registration is not allowed for this class. Please try again during regular registration. Prerequisites: STAT 350-0 and STAT 420-3