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STAA 552 - Generalized Regression Models

  • 2 credits

Categorical data analysis, estimation and testing for contingency tables, introduction to generalized linear models, logit and probit models for binary regression, extensions to nominal and ordinal multicategory responses, count data, Poisson and negative binomial regression, log-linear models.

If you should have any questions about this course offering, please contact Graduate & Online Program Coordinator, Alex Peitsmeyer.

Prerequisite

STAA 551 (Regression Models and Applications or concurrent registration) or Data Analysis and Regression; or written consent of instructor. This is a partial-semester course.

Important Information

Tuition includes access to lecture recordings which are available by streamed video. Lecture recordings may also be available by download or on DVD. To determine viewing options, contact the Department of Statistics degree program staff at stats_ddp@mail.colostate.edu. Visit the Department of Statistics website to learn more about what to do after registration, including creating your eID (if necessary) and accessing your course.

Instructors

Kirsten Eilertson
Kirsten Eilertson

9704916330 | kirsten.eilertson@colostate.edu

Kirsten Eilertson is originally from Minnesota. She earned her PhD in Statistics from Cornell University. She is an applied statistician, and has previously worked at The Gladstone Institutes at UC San Francisco and Penn State University. Her recent research has focused on modeling the impact of vaccination programs on disease burden in low- and middle-income countries. In her free time you may find her planning her next travel itinerary or hiking with her dog and husband, while optimistically anticipating The Winds of Winter by George R.R. Martin.