Consumers are often interested in the fuel efficiency of the vehicles they choose to buy, so much so that they will research the various models they consider buying. Fuel efficiency can depend on a variety of variables. In this analysis, there are 73 automobiles that are popular with consumers. A regression analysis has been performed; the dependent variable is CityMPG (EPA miles per gallon in city driving), and independent variables are Length (vehicle length in inches), Width (vehicle width in inches), Weight (vehicle weight in pounds), and ManTran (1 if manual shift transmission, 0 otherwise). The level of significance is 0.05. Use the following MegaStat output to answer questions about this regression analysis. a. State the regression equation. b. How would CityMPG be affected if the width of a vehicle increased by an inch? c. Estimate the CityMPG for a vehicle with a length of 190 inches, a width of 75 inches, a weight of 4100 pounds, and a manual. Round your answer to the nearest whole number. d. What is the critical value for the F test? e. Is the overall fit of the model significant or not? Explain your reasoning. f. Which predictors are significant and which are not? Explain your reasoning. g. What is the coefficient of determination and the adjusted coefficient of determination for your analysis? What do these two coefficients tell you about the variation of CityMPG in your model? Regression Analysis R² 0.771 Adjusted R² 0.758 n 73 R 0.878 k 4 Std. Error 2.401 Dep. Var. CityMPG ANOVA table Source SS df MS F p-value Regression 1,321.5861 4 330.3965 57.29 4.56E-21 Residual 392.1674 68 5.7672 Total 1,713.7534 72 Regression output confidence interval variables coefficients std. error t (df=68) p-value 95% lower 95% upper Intercept 56.3170 Length -0.0308 0.0181 -1.701 .0934 -0.0670 0.0053 Width -0.2189 0.1509 -1.450 .1517 -0.5201 0.0823 Weight -0.0036 0.0007 -4.889 6.50E-06 -0.0051 -0.0022 ManTran -0.8376 0.8057 -1.040 .3022 -2.4454 0.7701

Consumers are often interested in the fuel efficiency of the vehicles they choose to buy, so much so that they will research the various models they consider buying. Fuel efficiency can depend on a variety of variables. In this analysis, there are 73 automobiles that are popular with consumers. A regression analysis has been performed; the dependent variable is CityMPG (EPA miles per gallon in city driving), and independent variables are Length (vehicle length in inches), Width (vehicle width in inches), Weight (vehicle weight in pounds), and ManTran (1 if manual shift transmission, 0 otherwise). The level of significance is 0.05. Use the following MegaStat output to answer questions about this regression analysis. a. State the regression equation. b. How would CityMPG be affected if the width of a vehicle increased by an inch? c. Estimate the CityMPG for a vehicle with a length of 190 inches, a width of 75 inches, a weight of 4100 pounds, and a manual. Round your answer to the nearest whole number. d. What is the critical value for the F test? e. Is the overall fit of the model significant or not? Explain your reasoning. f. Which predictors are significant and which are not? Explain your reasoning. g. What is the coefficient of determination and the adjusted coefficient of determination for your analysis? What do these two coefficients tell you about the variation of CityMPG in your model? Regression Analysis R² 0.771 Adjusted R² 0.758 n 73 R 0.878 k 4 Std. Error 2.401 Dep. Var. CityMPG ANOVA table Source SS df MS F p-value Regression 1,321.5861 4 330.3965 57.29 4.56E-21 Residual 392.1674 68 5.7672 Total 1,713.7534 72 Regression output confidence interval variables coefficients std. error t (df=68) p-value 95% lower 95% upper Intercept 56.3170 Length -0.0308 0.0181 -1.701 .0934 -0.0670 0.0053 Width -0.2189 0.1509 -1.450 .1517 -0.5201 0.0823 Weight -0.0036 0.0007 -4.889 6.50E-06 -0.0051 -0.0022 ManTran -0.8376 0.8057 -1.040 .3022 -2.4454 0.7701

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Regression Analysis

	R²	0.771
	Adjusted R²	0.758	n	73
	R	0.878	k	4
	Std. Error	2.401	Dep. Var.	CityMPG

ANOVA table
Source	SS	df	MS	F	p-value
Regression	1,321.5861	4	330.3965	57.29	4.56E-21
Residual	392.1674	68	5.7672
Total	1,713.7534	72


Regression output				confidence interval
variables	coefficients	std. error	t (df=68)	p-value	95% lower	95% upper
Intercept	56.3170
Length	-0.0308	0.0181	-1.701	.0934	-0.0670	0.0053
Width	-0.2189	0.1509	-1.450	.1517	-0.5201	0.0823
Weight	-0.0036	0.0007	-4.889	6.50E-06	-0.0051	-0.0022
ManTran	-0.8376	0.8057	-1.040	.3022	-2.4454	0.7701