3 20 25 30 Predicted (mpg) 10 -8 Residuals (mpg) Residuals (mpg) Count
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Topic Video
Question
Fuel economy A consumer organization has reported
test data for 50 car models. We will examine the asso-
ciation between the weight of the car (in thousands of
ciation between the weight of the car (in thousands of
pounds) and the fuel efficiency (in miles per gallon).
Here are the scatterplot, summary statistics, and
regression analysis:Variable Count Mean StdDev
MPG 50 25.0200 4.83394
wt/1000 50 2.88780 0.511656
Dependent variable is: MPG
R-squared = 75.6%
s = 2.413 with 50 - 2 = 48 df
Variable Coefficient SE(Coeff) t-ratio P-value
Intercept 48.7393 1.976 24.7 ...0.0001
Weight -8.21362 0.6738 -12.2 ...0.0001
Here are the scatterplot, summary statistics, and
regression analysis:Variable Count Mean StdDev
MPG 50 25.0200 4.83394
wt/1000 50 2.88780 0.511656
Dependent variable is: MPG
R-squared = 75.6%
s = 2.413 with 50 - 2 = 48 df
Variable Coefficient SE(Coeff) t-ratio P-value
Intercept 48.7393 1.976 24.7 ...0.0001
Weight -8.21362 0.6738 -12.2 ...0.0001
a) Is there strong evidence of an association between the
weight of a car and its gas mileage? Write an appropri-
ate hypothesis.
ate hypothesis.
b) Are the assumptions for regression satisfied?
c) Test your hypothesis and state your conclusion.
c) Test your hypothesis and state your conclusion.
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