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 = -3.11+0.819HWY was previously determined to be the best for predicting city fuel consumption. A car weighs 2750 lb, it has an engine displacement of 2.2 L, and its highway fuel consumption is 35 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. Regression Table Predictor (x) Variables P-Value R² Adjusted R² WT/DISP/HWY WT/DISP 0.000 0.944 0.934 0.000 0.748 0.720 WT/HWY 0.000 0.942 0.936 |CITY=6.67 -0.00161WT+0.666HWY 0.000 0.935 0.928 0.000 0.712 0.697 0.000 0.659 0.641 0.000 0.924 0.920 DISP/HWY WT DISP HWY Regression Equation | CITY=6.86-0.00134WT-0.255DISP+0.656HWY | CITY=38.2-0.00161WT-1.31DISP | CITY=1.85-0.627DISP+0.703HWY |CITY=41.8-0.00609WT CITY=29.2-2.97DISP CITY = -3.11+0.819HWY X
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 = -3.11+0.819HWY was previously determined to be the best for predicting city fuel consumption. A car weighs 2750 lb, it has an engine displacement of 2.2 L, and its highway fuel consumption is 35 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. Regression Table Predictor (x) Variables P-Value R² Adjusted R² WT/DISP/HWY WT/DISP 0.000 0.944 0.934 0.000 0.748 0.720 WT/HWY 0.000 0.942 0.936 |CITY=6.67 -0.00161WT+0.666HWY 0.000 0.935 0.928 0.000 0.712 0.697 0.000 0.659 0.641 0.000 0.924 0.920 DISP/HWY WT DISP HWY Regression Equation | CITY=6.86-0.00134WT-0.255DISP+0.656HWY | CITY=38.2-0.00161WT-1.31DISP | CITY=1.85-0.627DISP+0.703HWY |CITY=41.8-0.00609WT CITY=29.2-2.97DISP CITY = -3.11+0.819HWY X
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
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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 = -3.11 +0.819HWY was previously determined to be the best for predicting
city fuel consumption. A car weighs 2750 lb, it has an engine displacement of 2.2 L, and its highway fuel consumption is 35 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.
Regression Table
Predictor (x) Variables P-Value R² Adjusted R²
0.000 0.944
WT/DISP/HWY
0.934
0.000 0.748 0.720
0.000 0.942 0.936
0.928
0.000 0.935
0.000 0.712
0.697
0.000
0.659
0.641
CITY=29.2-2.97DISP
0.000 0.924
0.920 CITY = -3.11 +0.819HWY
WT/DISP
WT/HWY
DISP/HWY
WT
DISP
HWY
Regression Equation
CITY=6.86 -0.00134WT-0.255DISP+0.656HWY
CITY=38.2-0.00161WT-1.31DISP
| CITY=6.67 -0.00161WT+0.666HWY
CITY = 1.85-0.627DISP+0.703HWY
CITY=41.8 -0.00609WT
-
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