A trucking company wants to predict the yearly maintenance expense (Y) for a truck using the number of miles driven during the year (X1) and the age of the truck (X2, in years) at the beginning of the year. The company has gathered the information given in the file P10_16.xlsx. Each observation corresponds to a particular truck.
a. Estimate a multiple regression equation using the given data.
b. Does autocorrelation appear to be a problem? What about multicollinearity? What about heteroscedasticity?
c. Find 95% confidence intervals for the regression coefficients of X1 and X2. Based on these interval estimates, which variable, if any, would you choose to remove from the equation estimated in part a? Why?