The editors of a national automotive magazine recently studied 30 different automobiles sold in the United States with the intent of seeing whether they could develop a multiple regression model to explain the variation in highway miles per gallon. A number of different independent variables were collected. The following regression output (with some values missing) was recently presented to the editors by the magazine's analysts:

Based on this output and your understanding of multiple regression analysis, what is the critical value for testing the significance of the overall regression model at a 0.05 level of statistical significance?

Nearly F= 3.80

About F = 5.92

Approximately F = 2.50

None of the above

 

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Regression Statistics Multiple R R Square Adjusted R Square Standard Error 0.906876 Observations 30 ANOVA df MS F Regression Residual 89.88341785 Total 506. 1666667 Coefficients Standard Error t Stat 5.612843566 0.00145286 0.887531206 P-value Lower 95%Upper 95% 41.77425 -0.00608 Intercept Curb Weight cylinders Horse Power Torque O to 60 mph Price as Tested Displacement 0.959134 0.052399 -0.01747 0.024737052 0.023938405 0.492998 -0.00015 -2.11223 0.486960357 4.31238E-05 0.88675014 Regression Statistics Multiple R R Square Adjusted R Square Standard Error 0.906876 Observations 30 ANOVA df MS F Regression Residual 89.88341785 Total 506. 1666667 Coefficients Standard Error t Stat 5.612843566 0.00145286 0.887531206 P-value Lower 95%Upper 95% 41.77425 -0.00608 Intercept Curb Weight cylinders Horse Power Torque O to 60 mph Price as Tested Displacement 0.959134 0.052399 -0.01747 0.024737052 0.023938405 0.492998 -0.00015 -2.11223 0.486960357 4.31238E-05 0.88675014

Answer rating: 100% (QA)

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