MATH 523 — Generalized Linear Models

Name: MATH 523 — Generalized Linear Models
Rating: 3.8 (95 reviews)

Exponential families, link functions. Inference and parameter estimation for generalized linear models; model selection using analysis of deviance. Residuals. Contingency table analysis, logistic regression, multinomial regression, Poisson regression, log-linear models. Multinomial models. Overdispersion and Quasilikelihood. Applications to experimental and observational data.

Rating: 3.80 out of 5 from 95 student reviews
Difficulty: 4.20 out of 5
Credits: 4
Faculty: Faculty of Science
Department: Mathematics and Statistics
Prerequisite: MATH 423 or MATH 533 or EPIB 697.