MATH 410A - Advanced Statistical Methods I

Description:
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).

Prerequisites:
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:
4/22/19

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