Using test data on 43 vehicles, an analyst fitted a regression to predict CityMPG (miles per gallon in city driving) using as predictors Length (length of car in inches). Width (width of car in inches), and Weight (weight of car in pounds). 8.682 Adjusted R2 R 8.658 43 k 3 CityMPG 8.826 Std. Error 2.558 Dep. Var. ANOVA table Source Regression Residual df p-value 8.35E-10 SS MS 547.3722 182.4574 27.90 255.0929 6.5408 882.4651 42 Regression output variables Intercept Length (in) Width (in) Weight (1bs) confidence interval Lipper 95% 55.9701 e.e982 Coefficients Std. Error t Stat p-Value Lower 95% VIF 39.4492 8.1678 4.830 e.ee0e 22.9283 e.8454 -0.035 e.9725 e.7379 -e.a016 -e.0934 2.669 e.1373 e.e008 -e.8463 -0.337 -0.3239 e.2314 2.552 -e.0043 -5.166 e.eeee -e.006e -e.ee26 2.836 (a) Referring to the Fstatistic and its p-value, what do you conclude about the overall fit of this model? The regression is significant O based on the Fcalc and pvalue (b) Do you see evidence that some predictors were unhelpful? (You may select more than one answer. Single cllck the box with the questlon mark to produce a check mark for a correct answer and double click the box with the question mark to empty the box for a wrong answer.) 2 Length Wiath 2 Weight (e) Do you suspect that multi-collinearity is a problem? O Yes No