Bus Modeling Using Regression

1.5 Credits · Level: Undergraduate

This elective offers a review of the essential principles and techniques of Least Squares Regression analysis. It emphasizes the rudiments of a forward-thinking, yet applied, Regression modeling course for the MSB Undergraduates. The course is designed to and has the objective of providing a practical approach to business applications using regression modeling, but not at the cost of the needed essential conceptual foundation. Topics include: Review of Simple (quick); Multiple linear Regression; Multi-collinearity and model impact; Residual analysis and lack of fit; Non-linear Transforms; Deviating from LSR model assumptions: Normality; Heteroscedasticity; Diagnostics and influential observations (jack knife), residual correlation (autocorrelation) and Durbin-Watson. Time allowing, other topics like, Logit Regression, will be addressed.