The accompanying table shows results from regressions per gal). The predictor (x) variables are WT (weight in pounds), DISP (engine displacement in liters), and HWY (highway fuel consumption in mi/gal). Which regression equation is best for predicting city fuel consumption? Why? Click the icon to view the table of regression equations. Choose the correct answer below. OA. The equation CITY= -3.12+0.824HWY is best because it has a low P-value and its R² and adjusted R² values are comparable to the R2 and adjusted R² values of equations with more predictor variables. OB. The equation CITY=6.88-0.00131WT-0.251DISP+0.654HWY is best because it has a low P-value and the highest value of R². OC. The equation CITY=6.65-0.00156WT +0.665HWY is best because it has a low P-value and the highest adjusted value of R². OD. The equation CITY=6.88-0.00131WT-0.251DISP+0.654HWY is best because it uses all of the available predictor variables.
The accompanying table shows results from regressions per gal). The predictor (x) variables are WT (weight in pounds), DISP (engine displacement in liters), and HWY (highway fuel consumption in mi/gal). Which regression equation is best for predicting city fuel consumption? Why? Click the icon to view the table of regression equations. Choose the correct answer below. OA. The equation CITY= -3.12+0.824HWY is best because it has a low P-value and its R² and adjusted R² values are comparable to the R2 and adjusted R² values of equations with more predictor variables. OB. The equation CITY=6.88-0.00131WT-0.251DISP+0.654HWY is best because it has a low P-value and the highest value of R². OC. The equation CITY=6.65-0.00156WT +0.665HWY is best because it has a low P-value and the highest adjusted value of R². OD. The equation CITY=6.88-0.00131WT-0.251DISP+0.654HWY is best because it uses all of the available predictor variables.
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
Question
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). Which regression equation is best for predicting city fuel consumption?
Why?
Click the icon to view the table of regression equations.
Choose the correct answer below.
OA. The equation CITY = -3.12 +0.824HWY is best because it has a low P-value and its R2 and adjusted R² values are comparable to the R2 and adjusted R2 values of equations with more
predictor variables.
OB. The equation CITY=6.88-0.00131WT-0.251DISP+0.654HWY is best because it has a low P-value and the highest value of R².
OC. The equation CITY = 6.65 -0.00156WT +0.665HWY is best because it has a low P-value and the highest adjusted value of R².
CITY=6.88-0.00131WT-0.251DISP+0.654HWY is best because it uses all of the available predictor variables.
OD. The equation
Regression Table
Predictor (x) Variables P-Value
WT/DISP/HWY
WT/DISP
WT/HWY
DISP/HWY
WT
DISP
HWY
R² Adjusted R²
0.000 0.944
0.000 0.747
0.000 0.943
0.000 0.935
0.000 0.712
0.000 0.659
0.000 0.924
0.934
0.719
0.937
0.928
0.697
0.641
0.920
Regression Equation
CITY=6.88-0.00131WT-0.251DISP+0.654HWY
CITY=37.7 -0.00156WT-1.35DISP
CITY=6.65-0.00156WT+0.665HWY
CITY=1.86-0.627DISP+0.709HWY
CITY 41.7-0.00604WT
CITY=28.7-3.03DISP
CITY=-3.12+0.824HWY
-
X
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