Math 4813  Regression Analysis

Text Applied Linear Statistical Models   4th edition

By    Neter,Kutner,Nachtsheim, and Wasserman

Credit   3 Hours

Prrequisite  Math 3063 or equivalent, Math 4113 or equivalent 

Description  In this course, simple linear regression as well as multiple regression will be studied. Attention will be given to methods of model building, diagnostics for examining the appropriateness of a model, and remedial measures that may be helpful when the model is not appropriate.  An understanding of  introductory statistical concepts is needed.


Material Covered


Linear Regression with one predictor variable

Inferences in Regression Analysis

Diagnostics and Remedial Measures

Simultaneous inferences

Multiple regression models

Coefficients of partial determination

Overview of model building

Diagnostics, DFFITS, DFBETAS, and Cook’s distance



Learning Outcomes


Students will identify appropriate regression models ( L5, L7, L12)

Students will use diagnostic techniques to identify violations of assumptions of a model. ( L11, L12)

Students will analyze residuals and their graphs to validate regression models. ( L5, L11)

Students will interpret coefficients of the models (L5, L11 )