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How much of the variance in the dependent variable does this regression model explain? SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Total Intercept X 12.98% 61.52% O 76.43% O 0.5956% 0.87428 0.76436 0.75983 0.05196 54 df 1 52 53 SS MS F 0.45532 0.45532 168.67823 0.00270 0.14037 0.59 Coefficients Standard Error t Stat 0.02173 4.52130 0.04743 12.98762 0.09827 0.61598 P-value 0.00004 0.00000 Significance F 5.97165E-18 Lower 95% 0.05465 0.52081 Upper 95% 0.14188 0.71115 A

How much of the variance in the dependent variable does this regression model explain? SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Total Intercept X 12.98% 61.52% O 76.43% O 0.5956% 0.87428 0.76436 0.75983 0.05196 54 df 1 52 53 SS MS F 0.45532 0.45532 168.67823 0.00270 0.14037 0.59 Coefficients Standard Error t Stat 0.02173 4.52130 0.04743 12.98762 0.09827 0.61598 P-value 0.00004 0.00000 Significance F 5.97165E-18 Lower 95% 0.05465 0.52081 Upper 95% 0.14188 0.71115 A

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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How much of the variance in the dependent variable does this regression model explain? SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Total Intercept X 12.98% 61.52% 76.43% 0.5956% 0.87428 0.76436 0.75983 0.05196 54 df 1 · 52 53 SS MS F 0.45532 0.45532 168.67823 0.14037 0.00270 0.59569 Coefficients Standard Error 0.09827 0.61598 t Stat 0.02173 4.52130 0.04743 12.98762 P-value 0.00004 0.00000 Significance F 5.97165E-18 Lower 95% 0.05465 0.52081 Upper 95% 0.14188 0.71115
Transcribed Image Text:How much of the variance in the dependent variable does this regression model explain? SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Total Intercept X 12.98% 61.52% 76.43% 0.5956% 0.87428 0.76436 0.75983 0.05196 54 df 1 · 52 53 SS MS F 0.45532 0.45532 168.67823 0.14037 0.00270 0.59569 Coefficients Standard Error 0.09827 0.61598 t Stat 0.02173 4.52130 0.04743 12.98762 P-value 0.00004 0.00000 Significance F 5.97165E-18 Lower 95% 0.05465 0.52081 Upper 95% 0.14188 0.71115
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