Question

PART III – Final Model Interpretations - Answer the following questions about your best model.

Least Squares Linear Regression of Price Predictor Variables       Coefficient   Std Error            T          P               VIF Constant            19375.2     1072.37         18.07 0.0000            0.0 Mileage             -0.05898     0.02835         -2.08   0.0430            1.1 Model               3315.29      642.703         5.16   0.0000            1.1 R²                     0.3648         Mean Square Error (MSE)            4734328 Adjusted R²   0.3378          Standard Deviation                       2175.85 AICc              774.31 PRESS          2.55E+08 Source           DF              SS                  MS                 F                P Regression   2         1.278E+08     6.390E+07    13.50         0.0000 Residual        47        2.225E+08     4734328 Total              49       3.503E+08 Cases Included 50    Missing Cases 0

1. Identify the least squares prediction equation (use #’s) for your best model after all your testing was completed (you do not need to show the printouts of any additional tests conducted, just the results of your best model). Use the values from the printout and write the prediction equation below. (3 points)

ŷ = 19375.2– 0.05898x1 + 3315.29x2

2. Interpret both s and R² associated with your best model. (4 points)

3. Would you use your model in practice? Why or why not? (3 points)

Answer 1