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Below is the output of a multiple model predicting car mileage per gallon (mpg) as a function of horsepower (hp) and weight (wt): How many observations were in the model? For the above model, calculate the adjusted R2 value (3 sig digits) For the above model, what is the value of the F-statistic corresponding to the omnibus test for the fit of the entire model? (3 sig digits)

Below is the output of a multiple model predicting car mileage per gallon (mpg) as a function of horsepower (hp) and weight (wt): How many observations were in the model? For the above model, calculate the adjusted R2 value (3 sig digits) For the above model, what is the value of the F-statistic corresponding to the omnibus test for the fit of the entire model? (3 sig digits)

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Below is the output of a multiple model predicting car mileage per gallon (mpg) as a function of horsepower (hp) and weight (wt):

How many observations were in the model?

For the above model, calculate the adjusted R2 value (3 sig digits)

For the above model, what is the value of the F-statistic corresponding to the omnibus test for the fit of the entire model? (3 sig digits)

Call: lm(formula Residuals: Min = mpg hp + wt, data 1Q Median 3Q Max -3.941 -1.600 -0.182 1.050 5.854 Coefficients: (Intercept) = hp wt mtcars) Estimate Std. Error t value Pr(>ltl) 37.22727 -0.03177 -3.87783 1.59879 23.285 < 2e-16 *** 0.00903 -3.519 0.00145 ** 0.63273 -6.129 1.12e-06 *** Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 0. Residual standard error: 2.593 on 29 degrees of freedom Multiple R-squared: 0.8268, Adjusted R-squared: 0.
Transcribed Image Text:Call: lm(formula Residuals: Min = mpg hp + wt, data 1Q Median 3Q Max -3.941 -1.600 -0.182 1.050 5.854 Coefficients: (Intercept) = hp wt mtcars) Estimate Std. Error t value Pr(>ltl) 37.22727 -0.03177 -3.87783 1.59879 23.285 < 2e-16 *** 0.00903 -3.519 0.00145 ** 0.63273 -6.129 1.12e-06 *** Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 0. Residual standard error: 2.593 on 29 degrees of freedom Multiple R-squared: 0.8268, Adjusted R-squared: 0.
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