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Table 2. Regression with seasonal dummies (Enrollment Bo + B1-Spring + B2•Fall + B3-Year) SUMMARY OUTPUT Regression Statistics Multiple R R Square Adj. R Square Standard Error ? Observations 6 ANOVA df SS MS Signif. F Regression 3 8590.667 515.44 0.001937 Residual ? ? Total 25805.33 Coefficients Stand. Error t Stat P-value Lower 95% Upper 95% Intercept 27 5.773503 4.676537 2.158623 51.84138 Spring 115 28.16913 0.001258 97.43449 132.5655 Fall 154 4.082483 ? 0.000702 136.4345 171.5655 Year ? 3.333333 -2.8 0.107393 -23.6755 5.008842

Table 2. Regression with seasonal dummies (Enrollment Bo + B1-Spring + B2•Fall + B3-Year) SUMMARY OUTPUT Regression Statistics Multiple R R Square Adj. R Square Standard Error ? Observations 6 ANOVA df SS MS Signif. F Regression 3 8590.667 515.44 0.001937 Residual ? ? Total 25805.33 Coefficients Stand. Error t Stat P-value Lower 95% Upper 95% Intercept 27 5.773503 4.676537 2.158623 51.84138 Spring 115 28.16913 0.001258 97.43449 132.5655 Fall 154 4.082483 ? 0.000702 136.4345 171.5655 Year ? 3.333333 -2.8 0.107393 -23.6755 5.008842

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. What is R2 and the standard error for the regression?

1a. What is your point estimate enrollment for Spring 2022?

Table 2. Regression with seasonal dummies (Enrollment = Bo + B1-Spring + B2-Fall + B3-Year) %3D SUMMARY OUTPUT Regression Statistics Multiple R R Square Adj. R Square Standard Error Observations 6. ANOVA df SS MS Signif. F Regression 3 ? 8590.667 515.44 0.001937 Residual 2 Total 5 25805.33 Coefficients Stand. Error t Stat P-value Lower 95% Upper 95% Intercept 27 5.773503 4.676537 ? 2.158623 51.84138 ? 28.16913 0.001258 ? 0.000702 Spring 115 97.43449 132.5655 Fall 154 4.082483 136.4345 171.5655 Year ? 3.333333 -2.8 0.107393 -23.6755 5.008842
Transcribed Image Text:Table 2. Regression with seasonal dummies (Enrollment = Bo + B1-Spring + B2-Fall + B3-Year) %3D SUMMARY OUTPUT Regression Statistics Multiple R R Square Adj. R Square Standard Error Observations 6. ANOVA df SS MS Signif. F Regression 3 ? 8590.667 515.44 0.001937 Residual 2 Total 5 25805.33 Coefficients Stand. Error t Stat P-value Lower 95% Upper 95% Intercept 27 5.773503 4.676537 ? 2.158623 51.84138 ? 28.16913 0.001258 ? 0.000702 Spring 115 97.43449 132.5655 Fall 154 4.082483 136.4345 171.5655 Year ? 3.333333 -2.8 0.107393 -23.6755 5.008842
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