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Following is a portion of the regression output for an application relating maintenance expense (dollars per month) to usage (hours per week) for a particular brand of computer termina Excel File: data14-41.xlsx 5.29 p-value= 0.01 Reject the null hypothesis Monthly maintenance expense is related c. Did the estimated regression equation provide a good fit? Yes ANOVA ▾to usage. Regression Residual Total Intercept Usage df 1 8 9 SS 1575.76 349.14 1924.90 Coefficients Standard Error 0.9361 0.149 6.1092 0.8951 MS t Stat If your answer is zero, enter "0". a. Write the estimated regression equation (to 4 decimals). ŷ6.1092+ 0.8951 * b. Use a t test to determine whether monthly maintenance expense is related to usage at the .05 level of significance (to 2 decimals, if necessary). Use Table 1 of Appendix B. t = F P-value Significance F

Following is a portion of the regression output for an application relating maintenance expense (dollars per month) to usage (hours per week) for a particular brand of computer termina Excel File: data14-41.xlsx 5.29 p-value= 0.01 Reject the null hypothesis Monthly maintenance expense is related c. Did the estimated regression equation provide a good fit? Yes ANOVA ▾to usage. Regression Residual Total Intercept Usage df 1 8 9 SS 1575.76 349.14 1924.90 Coefficients Standard Error 0.9361 0.149 6.1092 0.8951 MS t Stat If your answer is zero, enter "0". a. Write the estimated regression equation (to 4 decimals). ŷ6.1092+ 0.8951 * b. Use a t test to determine whether monthly maintenance expense is related to usage at the .05 level of significance (to 2 decimals, if necessary). Use Table 1 of Appendix B. t = F P-value Significance F

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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Following is a portion of the regression output for an application relating maintenance expense (dollars per month) to usage (hours per week) for a particular brand of computer terminal. Excel File: data14-41.xlsx Yes 5.29 ANOVA ▾to usage. Regression Residual Total Intercept Usage df 1 8 9 S.S 1575.76 349.14 1924.90 Coefficients Standard Error 0.9361 0.149 6.1092 0.8951 MS t Stat F If your answer is zero, enter "0". a. Write the estimated regression equation (to 4 decimals). ŷ = 6.1092 +0.8951 € b. Use a t test to determine whether monthly maintenance expense is related to usage at the .05 level of significance (to 2 decimals, if necessary). Use Table 1 of Appendix B. t= p-value = 0.01 Reject the null hypothesis Monthly maintenance expense is related c. Did the estimated regression equation provide a good fit? P-value Significance F
Transcribed Image Text:Following is a portion of the regression output for an application relating maintenance expense (dollars per month) to usage (hours per week) for a particular brand of computer terminal. Excel File: data14-41.xlsx Yes 5.29 ANOVA ▾to usage. Regression Residual Total Intercept Usage df 1 8 9 S.S 1575.76 349.14 1924.90 Coefficients Standard Error 0.9361 0.149 6.1092 0.8951 MS t Stat F If your answer is zero, enter "0". a. Write the estimated regression equation (to 4 decimals). ŷ = 6.1092 +0.8951 € b. Use a t test to determine whether monthly maintenance expense is related to usage at the .05 level of significance (to 2 decimals, if necessary). Use Table 1 of Appendix B. t= p-value = 0.01 Reject the null hypothesis Monthly maintenance expense is related c. Did the estimated regression equation provide a good fit? P-value Significance F
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