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Which statement best describes this regression where Y= highway miles per gallon (MPG) in 91 cars? R2 Adjusted R2 R Standard Error Source Regression Residual Total Multiple Choice 0.499 0.444 0.707 4.019 Dependent Variable SS 1,305.7251 1,308.3848 2,614.1099 n k df 9 81 90 MS 145.0806 16.1529 91 9 HwyMPG F 8.98 Regression is statistically significant but with large error in the MPG predictions. Regression is statistically significant and has quite small MPG prediction errors. Regression is not quite significant, but predictions should be very good. p-value .0000

Which statement best describes this regression where Y= highway miles per gallon (MPG) in 91 cars? R2 Adjusted R2 R Standard Error Source Regression Residual Total Multiple Choice 0.499 0.444 0.707 4.019 Dependent Variable SS 1,305.7251 1,308.3848 2,614.1099 n k df 9 81 90 MS 145.0806 16.1529 91 9 HwyMPG F 8.98 Regression is statistically significant but with large error in the MPG predictions. Regression is statistically significant and has quite small MPG prediction errors. Regression is not quite significant, but predictions should be very good. p-value .0000

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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Which statement best describes this regression where Y= highway miles per gallon (MPG) in 91 cars? R2 Adjusted R2 R Standard Error Source Regression Residual Total Multiple Choice 0.499 0.444 0.707 4.019 Dependent Variable SS 1,305.7251 1,308.3848 2,614.1099 n k df 9 81 90 MS 145.0806 16.1529 91 HwyMPG F 8.98 Regression is statistically significant but with large error in the MPG predictions. Regression is not quite significant, but predictions should be very good. Regression is statistically significant and has quite small MPG prediction errors. p-value .0000
Transcribed Image Text:Which statement best describes this regression where Y= highway miles per gallon (MPG) in 91 cars? R2 Adjusted R2 R Standard Error Source Regression Residual Total Multiple Choice 0.499 0.444 0.707 4.019 Dependent Variable SS 1,305.7251 1,308.3848 2,614.1099 n k df 9 81 90 MS 145.0806 16.1529 91 HwyMPG F 8.98 Regression is statistically significant but with large error in the MPG predictions. Regression is not quite significant, but predictions should be very good. Regression is statistically significant and has quite small MPG prediction errors. p-value .0000
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