3.00 Credits
Description: The focus of this course is on a careful understanding and presentation of regression models and associated methods of statistical inference, data analysis, interpretation of results, statistical computation, and model building. Topics covered include simple and multiple linear regression, correlation, residuals and diagnostics, model building/variable selection, and nonlinear regression. Students will gain hands-on experience with data analysis software such as R and/or SAS. Prerequisite: MATH 300 and MATH 341 OR graduate status. Notes: Offered in spring. Lab fee: $25.