Institutional Learning Outcomes: Knowledge Students are exposed to the concepts of regression analysis with an emphasis on application. Students will learn how to appropriately conduct residual analysis, perform diagnostics, apply transformations, select and check models, and augment regression such as with weighted least squares and nonlinear models. Students may learn additional topics such as inverse, robust, ridge and logistic regression. Prerequisite: MATH 1300 with a minimum C- grade or MATH 2121 with a minimum C- grade or MATH 2120 with a minimum C- grade and STAT 2000 with a minimum C- grade.
Institutional Learning Outcomes: Knowledge Students are exposed to the concepts of regression analysis with an emphasis on application. Students will learn how to appropriately conduct residual analysis, perform diagnostics, apply transformations, select and check models, and augment regression such as with weighted least squares and nonlinear models. Students may learn additional topics such as inverse, robust, ridge and logistic regression. Prerequisite: MATH 1300 with a minimum C- grade or MATH 2121 with a minimum C- grade or MATH 2120 with a minimum C- grade and STAT 2000 with a minimum C- grade.
