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STAA 552 - Generalized Regression Models

  • 2 credits
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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.


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 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.