Upon course completion, the student will be able to:
1. Understand and apply the general form of a multiple regression model, including model assumptions to solve management problems.2. Calculate a first-order regression model with quantitative predictors. Calculate the predictor variance, coefficient of determination and utility of the model using analysis of variance. Interpret results.
3. Apply regression model building utilizing quantitative and qualitative independent variables to reach appropriate solutions to management situations.
4. Apply stepwise regression techniques to a variety of cases and scenarios of management related problems. Interpret results.
5. Differentiate between the various regression models and identify the differences between other models and risks involved in the all-possible regression selection procedure.
6. Compare regression model results when deviating from assumptions, independent variable interaction is suspected, anomalies and lack of fit for residuals. Interpret results as a function of the assumptions used.
7. Use piecewise regression, weighted least squares and robust regression modeling techniques in practical applications.
8. Demonstrate an increased ability to recognize and apply appropriate statistical techniques to test inferential hypotheses and interpret results.