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This course reviews and extends knowledge and application of regression models. The course explores the ways in which multiple regression techniques allow for the analysis of the relationship between outcome and predictor variables while controlling for other variables. In doing so, students learn to build and evaluate multiple regression models using continuous outcome variables as well as logistic regression models using categorical outcome variables. Students gain applied experience fitting, visualizing, and interpreting regression models. The course also covers important topics in regression analysis including non-linear relationships, analysis of residuals, variable transformations, missing data, and multinomial logistic regression.

College/Department: School of Education
Repeat Status: Not repeatable for credit
Prerequisites: EDUC 835 [Min Grade: B]