Regression Statistics Multiple R 0.906876 R Square Adjusted R Square Standard Error Observations 30 ANOVA df SS MS F Reg

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Regression Statistics Multiple R 0 906876 R Square Adjusted R Square Standard Error Observations 30 Anova Df Ss Ms F Reg 1 (73.35 KiB) Viewed 90 times

Based on this output and your understanding of
multiple regression analysis
Compute Standard Error in the result (above)
A.
8
B.
1
C.
none
D.
4
E.
2

Regression Statistics Multiple R 0 906876 R Square Adjusted R Square Standard Error Observations 30 Anova Df Ss Ms F Reg 2 (73.57 KiB) Viewed 90 times

Based on this output and your understanding of
multiple regression analysis
Compute Standard Error in the result (above)
A.
8
B.
1
C.
none
D.
4
E.
2
Regression Statistics Multiple R 0.906876 R Square Adjusted R Square Standard Error Observations 30 ANOVA df SS MS F Regression Residual Total 89.88341785 506.1666667 1 Stat P-value Lower 95% Upper 95% Intercept Curb Weight cylinders Horse Power Torque 0 to 60 mph Price as Tested Displacement Coefficients Standard Error 41.77425 5.612843566 -0.00608 0.00145286 0.959134 0.887531206 0.052399 0.023938405 -0.01747 0.024737052 0.492998 0.486960357 -0.00015 4.31238E-05 -2.11223 0.88675014

Regression Statistics Multiple R 0.906876 R Square Adjusted R Square Standard Error Observations 30 ANOVA df SS MS F Regression Residual Total 89.88341785 506.1666667 + Stat P-value Lower 95% Upper 95% Intercept Curb Weight cylinders Horse Power Torque 0 to 60 mph Price as Tested Displacement Coefficients Standard Error 41.77425 5.612843566 -0.00608 0.00145286 0.959134 0.887531206 0.052399 0.023938405 -0.01747 0.024737052 0.492998 0.486960357 -0.00015 4.31238E-05 -2.11223 0.88675014