Feb 22, 2024  
2020-2021 Undergraduate Catalog 
2020-2021 Undergraduate Catalog [ARCHIVED CATALOG]

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MATH 410A - Advanced Statistical Methods I

An introduction to generalized linear models, including multiple regression, logistic regression, and ANOVA.  Emphasis on applied model evaluation and diagnostics. Course will be offered every year (Fall, Winter).

Prerequisite: MATH 211 or MATH 314 with a grade of C or higher.

Credits: (4)

Learner Outcomes:
Upon successful completion of this course, the student will be able to:

  • Evaluate theoretical properties of generalized linear models, including underlying model assumptions and model construction.
  • Choose an appropriate generalized linear model, including appropriate choices of distribution, link function, transformations, and interactions.
  • Estimate generalized linear models.
  • Evaluate the appropriateness and fit of a statistical model, particularly generalized linear models, and interpret the model in context.
  • Estimate ANOVA models, and interpret the results.
  • Propose a major statistical project, choosing appropriate questions to be answered and appropriate statistical tools.
  • Communicate statistical results clearly orally and in writing.

Learner Outcomes Approval Date:

Anticipated Course Offering Terms and Locations:
Fall Locations: Ellensburg Winter Locations: Ellensburg

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