Regression Statistics 0.994215326 0.988464115 0.985580144 3.96139482 Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Total Intercept X Variable 1 df 6 SS MS F Significance F 1 5378.562738 5378.563 342.7441 5.00969E-05 4 62.77059569 15.69265 5 5441.33333 Coefficients Standard Errort Stat P-value Lower 95% 91.99493029 4.936028654 18.63744 4.88E-05 78.2903177 1.279087452 0.069090009 18.51335 5.01E-05 1.087262835 Upper 95% 105.699542 1.4709120

Regression Statistics 0.994215326 0.988464115 0.985580144 3.96139482 Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Total Intercept X Variable 1 df 6 SS MS F Significance F 1 5378.562738 5378.563 342.7441 5.00969E-05 4 62.77059569 15.69265 5 5441.33333 Coefficients Standard Errort Stat P-value Lower 95% 91.99493029 4.936028654 18.63744 4.88E-05 78.2903177 1.279087452 0.069090009 18.51335 5.01E-05 1.087262835 Upper 95% 105.699542 1.4709120

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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Calculate two lines of regression and calculate a linear regression equation to model the data given below: years (1980,1985,1990,1995,2000) Enrolment ( 21,25,29,39,47)
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This was not the correct quadratic model for the data
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