Refer to Problem 14. Using the computer output for that problem, and the accompanying output here, answer the following questions.
a. Determine the variance inflation factors for the estimated model in part (b) of Problem 14. Does collinearity appear to be a problem?
b. Determine the estimated equation of the quadratic regression of the number of customers applying for the discount (Y) on the centered discount level (Z).
c. Determine the variance inflation factors for the estimated model in part (b) of this problem. Does collinearity appear to be a problem?
d. Conduct variables-added-in-order tests for the model in part (b).
e. Carry out tests for the significance of the quadratic regression in part (b) and for the adequacy of fit of the second-order model.
f. Based on the results from Problem 14 and parts (a) through (e) of this problem, which of the two regressions appears to be more appropriate for predicting the number of customers who apply for the discount?

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Root MSE Dependent Mean Coeff Var 199.28707 1530.41667 13.02175 R-Square Adj R-Sq 0.9242 0.9074 PARAMETER ESTIMATES Parameter Variance Standard Error Variable DF Estimate Intercept t Value Pr> Infiation 1408.85417 92.09169 15.30 $,0001 106.42000 10.29114 10340001 1.69 0.1252 1.00000 3.89000 2.30117 1.00000 Quadratic regression of Y on X Type I Sum of Squares R-Square F Value Pr>F 106.93 000 Regression Linear Quadratic Total Model DF 4246956 113491 4360447 0.9002 0.0241 0.9242 54.90 <0001 2.86 0.1252 2 Sum of DF Squares Mean Square FValue Pr > F Residual Lack of Fit Pure Error Total Error 39990 39681 39715 01 0.3448 39990 317448 357438 8 9