StatisticsSTAT 209 Generalized Linear Models

Theory, methods, and applications of generalized linear statistical models; review of linear models; binomial models for binary responses (including logistical regression and probit models); log-linear models for categorical data analysis; and Poisson models for count data. Case studies drawn from social, engineering, and life sciences. (Formerly AMS 274.)

Requirements

Prerequisite(s): STAT 205B or STAT 256. Enrollment is restricted to graduate students.

Credits

5

Quarter offered

Fall

Instructor

The Staff, Athanasios Kottas