MATH 330 - Regression Models in Business and Social Science

3 Credit(s)

Applied statistical analysis techniques including multiple regression and associated topics, categorical variables, and logistic regression. Applications involving the use of statistical software and cross-disciplinary datasets are an integral part of the course. Not recommended for first year students.

Prerequisite(s): MATH 140

Course Frequency: ALT F (odd years)

Grading Method: Student option.

Learning Outcomes:

Generate and interpret diagnostic statistics and plots for both bivariate and multiple regression models.
Determine which independent variables to include in a regression model and their functional forms.
Perform regression tests involving multicollinearity, interactions, and categorical variables.