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). R2 0. 682 Adjusted R2 0. 658 n 43 R 0. 826 k 3 Standard error 2. 558 Dependent variable CityMPG ANOVA table Source 55 df MS F p- value Regression 547.3722 3 182 . 4574 27.90 8. 35E- 10 Residual 255.0929 39 6.5408 802.4651 42 Regression output confidence interval variables Coefficients Standard error t statistic p- Value Lower 95% Upper 95% VIF Intercept 39. 4492 8. 1678 4.830 0.0000 22.9283 55.9701 Length (in) -0. 0016 0. 0454 -0.035 0. 9725 -0. 0934 0. 0902 2. 669 Width (in) -0. 0463 0. 1373 -0.337 0. 7379 -0. 3239 0. 2314 2. 552 Weight (1bs) -0. 0043 0. 0008 -5.166 0. 0000 -0. 0060 -0. 0026 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 based on the Fcalc and p-value(b) Do you see evidence that some predictors were unhelpful? (You may select more than one answer. Single click the box with the question 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. Any boxes left with a question mark will be automatically graded as incorrect.) 9 Length (c) Do you suspect that multircoillinearity is a problem? 0 Yes ONO