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Predictors with α = 0.05 Which predictors do you consider significant? Which predictors would you be comfortable eliminating?

Predictors with α = 0.05 Which predictors do you consider significant? Which predictors would you be comfortable eliminating?

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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  1. Predictors with α = 0.05

Which predictors do you consider significant?

Which predictors would you be comfortable eliminating?

SUMMARY OUTPUT Regression Statistics Multiple R 0.9761368 R Square 0.9528431 Adjusted R Sc 0.9486514 Standard Erro 84.864073 Observations 50 ANOVA df SS MS Significance F Regression 4 6548422 1637105.5 227.31543 3.205E-29 Residual 45 324085.99 7201.9109 Total 49 6872508 Coefficients tandard Erroi t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 19.520368 56.459619 0.3457403 0.731149 -94.195142 133.23588 -94.195142 133.23588 Floor Area (Se 0.259969 0.0182476 14.246738 2.74E-18 0.2232164 0.2967216 0.2232164 0.2967216 Offices 74.272247 26.009425 2.8555897 0.006477 21.886575 126.65792 21.886575 126.65792 Entrances 49.31807 29.007488 1.7001841 0.095999 -9.1060107 107.74215 -9.1060107 107.74215 Age 0.9423287 0.9766529 0.9648553 0.3397741 -1.0247512 2.9094087 -1.0247512 2.9094087 Е. What is the R2? What is the adjusted R2? Explain the purpose of having an adjusted R2?
Transcribed Image Text:SUMMARY OUTPUT Regression Statistics Multiple R 0.9761368 R Square 0.9528431 Adjusted R Sc 0.9486514 Standard Erro 84.864073 Observations 50 ANOVA df SS MS Significance F Regression 4 6548422 1637105.5 227.31543 3.205E-29 Residual 45 324085.99 7201.9109 Total 49 6872508 Coefficients tandard Erroi t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 19.520368 56.459619 0.3457403 0.731149 -94.195142 133.23588 -94.195142 133.23588 Floor Area (Se 0.259969 0.0182476 14.246738 2.74E-18 0.2232164 0.2967216 0.2232164 0.2967216 Offices 74.272247 26.009425 2.8555897 0.006477 21.886575 126.65792 21.886575 126.65792 Entrances 49.31807 29.007488 1.7001841 0.095999 -9.1060107 107.74215 -9.1060107 107.74215 Age 0.9423287 0.9766529 0.9648553 0.3397741 -1.0247512 2.9094087 -1.0247512 2.9094087 Е. What is the R2? What is the adjusted R2? Explain the purpose of having an adjusted R2?
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