24 2 points How do you interpret the R-squared for the following Printout? Least Squares Linear Regression of Price Predictor Variables Coefficient Std Errong VIF Constant 18873.4 824.019 22 90 0,0000 0.0 Mileage 0.08463 0.01489 -5.68 0.0009 19 Model 2072+04 1144.32 1 81 0.0767 RZ 0.6403 Mean Square Error (MSE) 5449993 Adjusted R 0.6169 Standard Deviation 2334.52 AICC 782.75 PRESS 2. 89E+08 Source DF SS MS Regression 3 4.4636+08 1.488E+08 27.30 Residual 46 2. 507E+08 5449993 Total 49 6.970E+08 Lack of Fit 43 2, 3026+08 5353481 0.78 0. 7055 Pure Error 3 2. 050E+07 6833333 Cases Included 50 Missing Cases 0 We can predict the price of a vehicle within $2334 when using the model with mileage and model OO 6 We can predict the mileage of a vehicle within 2334 when using the model with price and model We can explain 64% of the variation in vehicle price around the mean using the model with mileage and model 7 O We can explain 64% of the variation, in vehicle mileage around the mean using the model with price and model 8