Use the output below to answer questions 8 through 12. The model is trying to pr

Question

Use the output below to answer questions 8 through 12. The model is trying to predict traffic delays/person for different cities, based on city characteristics: city size (S, M, L, XL), and average highway and arterial speeds. Assume all regression assumptions are met. Statistics Multiple R R Square 0.889127899 0.790548421 Adjusted R Square 0.773657165 Standard Error 6.474064904 68 ANOVA MS ance F 5 9808.229632 1961.64592646.802227 8.81035E-20 Residual Total 62 2598.638015 41.91351638 67 12406.86765 Intercept HiWay MPH Arterial MPH Small Large Very Large Coefficients Standard Error tStat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 139.1041107 16.69063456 8.334261358 1.043E-11 105.7400079 172.4682135 105.7400079 172.4682135 1.073471854 0.247420454 -4.33865445 5.379E-05 -1.56805829-0.578885418 1.56805829-0.578885418 04836152 0.667165757-3.0702437870.0031727-3.382006852 0.714716188-3.382006852-0.714716188 3.589696886 2.953037124-12155949060.2287478-9.492733928 2.313340156-9.492733928 2.313340156 5.009669683 2.103615129 2.3814573370.0203282 0.804602997 9.214736368 0.804602997 9.214736368 3,410579515 3.229696038 1.0560063470.2950629-3.045490811 9.866649841-3.045490811 9.866649841

Explanation / Answer

Adjusted R square of Model 1 is high

MSE of model 1 is low.

So I would prefer model 1 over model 2

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