Problem 1: Model 1 Regression Statistics Multiple R 0.7581 R Square 0.5747 Adjusted R Square 0.5039 Standard Error 5.7825 Observations 29 ANOVA Df SS MS F 4 8.1089 Regression Residual 1084.5500 802.4845 271.1375 33.4369 24 Total 28 1887.0345 Standard Error T Stat P-value Coefficients 101.5132 21.0405 4.8247 0.0001 -2.4013 0.0031 Intercept Curb Weight (lb) Engine Type Transmission Type TopSpeed (mph) -0.0065 2.9392 0.0027 2.8835 1.0193 0.1554 2.0008 -2.0968 0.0477 -4.1952 0.2040 0.0846 2.4113 0.0240 Problem 1: Model 2 In the second model, two new variables: ZeroTo60 - time to go from 0 to 60 mph (seconds), and HorsePower - horse power along with the variables entered in model 1 were used as independent variables with speed at %4 mile as the dependent variables. The following table shows the Excel output for this model (refer to this output as model 2). Regression Statistics Multiple R 0.9345 R Square 0.8734 Adjusted R Square 0.8388 Standard Error 3.2957 Observations 29 ANOVA Df SS MS F Significance F 8.1843E-09 6 1648.0738 274.6790 25.2884 Regression Residual 22 238.9607 10.8618 Total 28 1887.0345 Standard Error 1 Stat P-value Coefficients 151.0469 -0.0078 0.0000 14.3539 0.0022 10.5231 -3.5746 0.0017 1.8564 1.6649 1.1.150 0.2769 Intercept Curb Weight Engine Type Transmission Type TopSpeed ZeroTo60 -2.9906 1.6375 -1.8263 0.0814 0.3940 -0.0584 0.0672 -0.8694 -4.8289 1.8446 -2.6178 0.0157 HorsePower 0.0516 0.0171 3.0068 0.0065 Answer the following questions by evaluating the relevant output (model 1 and 2) Is the revised model (model 2) with the variables ZeroTo60 and Horsepower better than the original model (model 1)? Why or why not? (5 points)