The accompanying table shows results from regressions performed on data from a random sample of 21 cars. The response (y) variable is CITY (fuel consumption in mi/gal). The predictor (x) variables are WT (weight in pounds), DISP (engine displacement in liters), and HWY (highway fuel consumption in mi/gal). The equation CITY= -3.14+0.818HWY was previously determined to be the best for predicting city fuel consumption. A car weighs 2760 lb, it has an engine displacement of 2.2 L, and its highway fuel consumption is 34 mi/gal. What is the best predicted value of the city fuel consumption? Is that predicted value likely to be a good estimate? Is that predicted value likely to be very accurate? Click the icon to view the table of regression equations. The best predicted value of the city fuel consumption is 24.672 mi/gal. (Type an integer or a decimal. Do not round.) The predicted value is likely to be a good estimate and is not likely to be very accurate because the sample consists of only 21 cars. Regression Table Predictor (x) Variables P-Value WT/DISP/HWY WT/DISP WT/HWY DISP/HWY WT DISP HWY R² Adjusted R² 0.943 0.000 0.000 0.747 0.000 0.941 0.000 0.936 0.000 0.712 0.000 0.659 0.000 0.924 0.933 0.719 0.934 0.929 0.697 0.641 0.920 Regression Equation CITY=6.89-0.00133WT-0.255DISP+0.652HWY CITY=37.8-0.00159WT-1.34DISP CITY=6.67 -0.00159WT +0.665HWY CITY=1.83-0.626DISP+0.703HWY CITY=42.2-0.00609WT CITY=28.8-2.95DISP CITY=-3.14+0.818HWY - X

MATLAB: An Introduction with Applications
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ISBN:9781119256830
Author:Amos Gilat
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Chapter1: Starting With Matlab
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The accompanying table shows results from regressions performed on data from a random sample of 21 cars. The response (y) variable is CITY (fuel consumption in mi/gal). The predictor (x)
variables are WT (weight in pounds), DISP (engine displacement in liters), and HWY (highway fuel consumption in mi/gal). The equation CITY = -3.14+0.818HWY was previously determined to be
the best for predicting city fuel consumption. A car weighs 2760 lb, it has an engine displacement of 2.2 L, and its highway fuel consumption is 34 mi/gal. What is the best predicted value of the city
fuel consumption? Is that predicted value likely to be a good estimate? Is that predicted value likely to be very accurate?
Click the icon to view the table of regression equations.
The best predicted value of the city fuel consumption is 24.672 mi/gal.
(Type an integer or a decimal. Do not round.)
The predicted value is
likely to be a good estimate and is not likely to be very accurate because the sample consists of only 21 cars.
Regression Table
Predictor (x) Variables P-Value R² Adjusted R²
WT/DISP/HWY
WT/DISP
WT/HWY
0.000 0.943
0.000 0.747
0.000 0.941
0.000 0.936
0.000 0.712
DISP/HWY
WT
0.000
0.659
0.000 0.924
DISP
HWY
0.933
0.719
0.934
0.929
0.697
0.641
0.920
Regression Equation
CITY = 6.89 -0.00133WT -0.255DISP+ 0.652HWY
CITY = 37.8 -0.00159WT - 1.34DISP
CITY = 6.67 -0.00159WT +0.665HWY
CITY = 1.83 -0.626DISP+ 0.703HWY
CITY = 42.2 -0.00609WT
CITY=28.8-2.95DISP
CITY - 3.14 +0.818HWY
I
X
Transcribed Image Text:The accompanying table shows results from regressions performed on data from a random sample of 21 cars. The response (y) variable is CITY (fuel consumption in mi/gal). The predictor (x) variables are WT (weight in pounds), DISP (engine displacement in liters), and HWY (highway fuel consumption in mi/gal). The equation CITY = -3.14+0.818HWY was previously determined to be the best for predicting city fuel consumption. A car weighs 2760 lb, it has an engine displacement of 2.2 L, and its highway fuel consumption is 34 mi/gal. What is the best predicted value of the city fuel consumption? Is that predicted value likely to be a good estimate? Is that predicted value likely to be very accurate? Click the icon to view the table of regression equations. The best predicted value of the city fuel consumption is 24.672 mi/gal. (Type an integer or a decimal. Do not round.) The predicted value is likely to be a good estimate and is not likely to be very accurate because the sample consists of only 21 cars. Regression Table Predictor (x) Variables P-Value R² Adjusted R² WT/DISP/HWY WT/DISP WT/HWY 0.000 0.943 0.000 0.747 0.000 0.941 0.000 0.936 0.000 0.712 DISP/HWY WT 0.000 0.659 0.000 0.924 DISP HWY 0.933 0.719 0.934 0.929 0.697 0.641 0.920 Regression Equation CITY = 6.89 -0.00133WT -0.255DISP+ 0.652HWY CITY = 37.8 -0.00159WT - 1.34DISP CITY = 6.67 -0.00159WT +0.665HWY CITY = 1.83 -0.626DISP+ 0.703HWY CITY = 42.2 -0.00609WT CITY=28.8-2.95DISP CITY - 3.14 +0.818HWY I X
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