Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Total Obs. Intercept Xx HN Part I: Regression Basics SUMMARY OUTPUT A 1 2 3 Regression Statistics st 4 X556 8 0.97688814 df 0.939080583 3.277208147 5 1 3 4 Data Y 23 16 25 28 SS 672.9797 32.22028 Y hat Standard Error Coefficients t Stat P-value 2.531468531 3.604616 0.702285 0.533087 3.43006993 0.433317 7.915839 0.004203
Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Total Obs. Intercept Xx HN Part I: Regression Basics SUMMARY OUTPUT A 1 2 3 Regression Statistics st 4 X556 8 0.97688814 df 0.939080583 3.277208147 5 1 3 4 Data Y 23 16 25 28 SS 672.9797 32.22028 Y hat Standard Error Coefficients t Stat P-value 2.531468531 3.604616 0.702285 0.533087 3.43006993 0.433317 7.915839 0.004203
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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Step 1
Data given
Coefficient of intercept=2.531468531
Coefficient of X =3.43006993
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