6 2 points What would you conclude from the following Printout? Least Squares Linear Regression of Price Predictor Variables Coefficient Std Error T P VIF Constant 18873.4 824. 019 22 .90 0.0000 0.0 Mileage -0.08463 0. 01489 -5.68 0.0000 1.9 Model 2072.04 1144.32 1 81 0.0767 3.0 X1X2 -0.01983 0.00655 -3. 03 0.0028 3.6 RZ 0.6403 Mean Square Error (MSE) 5449993 Adjusted Rz 0.6169 Standard Deviation 2334. 52 AICC 782.75 PRESS 2. 89E+08 Source DF SS MS F P Regression 3 4.463E+08 1.488E+08 27.30 0.0000 Residual 46 2. 5078+08 5449993 Total 49 6.970E+08 Lack of Fit 43 2. 302E+08 5353481 0.78 0.7055 Pure Error 3 2.0508+07 6833333 Cases Included 50 Missing Cases 0 O There is insufficient evidence that there is an interaction between mileage and model There is sufficient evidence that there is an interaction between mileage and model O There is sufficient evidence that this is a curvilinear relationship O There is insufficient evidence that any of the independent variables in this model are useful in predicting price 7 2 poi