APPLIED REGRESSION ANALYSIS
2017 Fall Term
This is a second course in regression analysis and its applications. Topics include correlation, simple and multiple linear regression, model assumptions, inference of regression parameters, regression diagnostics and remedial measures, categorical predictors, multicollinearity,and model selection. Real data re emphasized and analyzed using statistical software such as R or SAS.
Other Requirements: PREREQ: MATH 342 OR CONSENT OF INSTRUCTOR
There are no sections offered for this course and term that meet your criteria.