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) R 2 0 682 Adjusted R 2 0 658 n 43 R 0 826 k 3 Std Error 2 558 Dep Var CityMPG ANOVA table Source SS 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 Std Error t Stat 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 (lbs) 0 0043 0 0008 5 166 0 0000 0 0060 0 0026 2 836 (a) Referring to the F statistic and its p value, what do you conclude about the overall fit of this model The regression is (Click to select) significant insignificant based on the F calc 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 ) check all that apply Lengthunanswered Widthunanswered Weightunanswered (c) Do you suspect that multi colllinearity is a problem multiple choice 2 Yes No

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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

Using test data on 43 vehicles, an analyst fitted a regression to predictCityMPG(miles per gallon in city driving) using as predictorsLength(length of car in inches),Width(width of car in inches), andWeight(weight of car in pounds).


R²	0.682
Adjusted R²	0.658	n	43
R	0.826	k	3
Std. Error	2.558	Dep. Var.	CityMPG

ANOVA table
Source	SS		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	Std. Error		t Stat	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 (lbs)	0.0043		0.0008		5.166		0.0000		0.0060	0.0026	2.836

(a)Referring to theF_statisticand itsp-value, what do you conclude about the overall fit of this model? The regression is (Click to select) significant insignificant based on theF_calcandp-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.) check all that apply