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QUESTION 8 h) What is the R Square of this model? What does it mean? Use the information in ANOVA table to calculate R square.

QUESTION 8 h) What is the R Square of this model? What does it mean? Use the information in ANOVA table to calculate R square.

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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QUESTION 8 h) What is the R Square of this model? What does it mean? Use the information in ANOVA table to calculate R square. For the toolbar, press ALT+F10 (PC) or ALT+FN+F10 (Mac).
Transcribed Image Text:QUESTION 8 h) What is the R Square of this model? What does it mean? Use the information in ANOVA table to calculate R square. For the toolbar, press ALT+F10 (PC) or ALT+FN+F10 (Mac).
The following sample data contains the number of years of college and the current annual salary for a random sample of heavy equipment salespeople. A researcher believes that spending more years in college leads to higher annual income. (80 points) Annual Income Years in College (In Thousands) 31.2 2 35.9 39.0 54.6 4 43.7 3 28.1 57.7 4 46.8 3 62.4 4 60.8 SUMMARY OUTPUT Regression Statistics Multiple R 0.959 R Square 0.919 Adjusted R Square 0.909 Standard Error 3.756 Observations 10.000 ANOVA df SS MS F Significance F Regression 1.000 1,285.245 1,285.245 91.105 0.000 Residual 8.000 112.858 14.107 Total 9.000 1,398.103 Lower 95% Upper 95% Lower 95.0% Upper 95.0% (1.591) 9.613 Coefficients itandard Erroi t Stat P-value Intercept 7.995 4.157 1.923 0.091 17.581 (1.591) 17.581 Years in College 12.675 1.328 9.545 0.000 15.737 9.613 15.737
Transcribed Image Text:The following sample data contains the number of years of college and the current annual salary for a random sample of heavy equipment salespeople. A researcher believes that spending more years in college leads to higher annual income. (80 points) Annual Income Years in College (In Thousands) 31.2 2 35.9 39.0 54.6 4 43.7 3 28.1 57.7 4 46.8 3 62.4 4 60.8 SUMMARY OUTPUT Regression Statistics Multiple R 0.959 R Square 0.919 Adjusted R Square 0.909 Standard Error 3.756 Observations 10.000 ANOVA df SS MS F Significance F Regression 1.000 1,285.245 1,285.245 91.105 0.000 Residual 8.000 112.858 14.107 Total 9.000 1,398.103 Lower 95% Upper 95% Lower 95.0% Upper 95.0% (1.591) 9.613 Coefficients itandard Erroi t Stat P-value Intercept 7.995 4.157 1.923 0.091 17.581 (1.591) 17.581 Years in College 12.675 1.328 9.545 0.000 15.737 9.613 15.737
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