Applied Regression Methods
General
Prefix
STAT
Course Number
521
Course Level
Graduate
Department/Unit(s)
College/School
College of Science and Engineering
Description
Advanced regression methods focused on complex real-world data. Model checking and diagnostics, model building, transformations, polynomial regression, logistic regression, general linear models, nonparametric regression methods.
Prerequisites
Credits
Min
3
Max
3
Repeatable
No
Goals and Diversity
MN Goal Course
No
Cultural Diversity
No
Learning Outcomes
Outcome
Determine meaning and perform computation of regression coefficients and diagnostics.
Outcome
Select the best regression equation based on a given criterion.
Outcome
Use computer software to perform a variety of regression analysis and ANOVA.
Outcome
Apply inferential methods to test hypotheses in regression and a variety of ANOVA problems.
Outcome
Use the logistic regression analysis for binary response data.
Outcome
Analyze the connections between the learning outcomes of this course and the larger picture of undergraduate statistics and the student's own experience, or explore a subset of course topics in greater depth than what is required for the typical undergraduate student, or both.