Using test data on 43 vehicles, an anaiyst fitted a regression to predict CityMPG (miles per...

Transcribed Image Text:

Using test data on 43 vehicles, an anaiyst 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 8.682 Adjusted R2 0.658 43 n 0.826 k 3 Std. Error 2.558 Dep. Var. CityMPG ANOVA table SS df MS p-value 8.35E-10 Source Regression Residual 547.3722 182.4574 27.90 255.0929 39 6.5408 802.4651 42 confidence interval Upper 95% 55.9701 0.8902 8.2314 Regression output variables Coefficients 39.4492 t Stat 4.830 -0.035 Std. Error p-Value e.ee00 Lower 95% 22.9283 -0.0934 VIF Intercept Length (in) Width (in) Weight (1bs) 8.1678 0.0454 0.9725 8.7379 -0.0016 2.669 -0.0463 0.1373 -0.337 -0.3239 2.552 -0.0043 0.0008 -5.166 0.0e0e -0.8060 -e.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 significant 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 cllck the box with the questlon mark to produce a check mark for a correct answer and double click the box with the questlon mark to empty the box for a wrong answer.) 7 Length 2 Width 2 Welght (c) Do you suspect that multi-colllinearity is a problem? Yes No Using test data on 43 vehicles, an anaiyst 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 8.682 Adjusted R2 0.658 43 n 0.826 k 3 Std. Error 2.558 Dep. Var. CityMPG ANOVA table SS df MS p-value 8.35E-10 Source Regression Residual 547.3722 182.4574 27.90 255.0929 39 6.5408 802.4651 42 confidence interval Upper 95% 55.9701 0.8902 8.2314 Regression output variables Coefficients 39.4492 t Stat 4.830 -0.035 Std. Error p-Value e.ee00 Lower 95% 22.9283 -0.0934 VIF Intercept Length (in) Width (in) Weight (1bs) 8.1678 0.0454 0.9725 8.7379 -0.0016 2.669 -0.0463 0.1373 -0.337 -0.3239 2.552 -0.0043 0.0008 -5.166 0.0e0e -0.8060 -e.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 significant 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 cllck the box with the questlon mark to produce a check mark for a correct answer and double click the box with the questlon mark to empty the box for a wrong answer.) 7 Length 2 Width 2 Welght (c) Do you suspect that multi-colllinearity is a problem? Yes No