Suppose the athletic director at Villanova University would like to develop a regression model to predict the point differential for games played by the college’s men’s basketball team. A point differential is the difference between the final points scored by two competing teams. A positive differential is a win for Villanova, and a negative differential is a loss. For a random sample of games, shown in the Excel file Villanova basketball 1. xlsx, the point differential was calculated for Villanova, along with the number of assists, rebounds, turnovers, and personal fouls.
a. Using PHStat, check for the presence of multicollinearity.
b. If multicollinearity is present, take the necessary steps to eliminate it.
c. Perform a best subsets regression and choose the most appropriate model for these data.
d. Identify the regression equation for the model in part c.
e. Perform a residual analysis with the model in part c to verify that the conditions for the model are met.