A1 fe ANOVA A. B E F G 1 ANOVA 2 df Significance F MS 3 Regression 4 Residual 5 Total 1 1575.76 8 349.14 1924.90 6 7 Coefficients Standard Error t Stat P-value 8 Intercept 6.1092 0.9361 9 Usage 0.8951...

Extracted text: A1 fe ANOVA A. B E F G 1 ANOVA 2 df Significance F MS 3 Regression 4 Residual 5 Total 1 1575.76 8 349.14 1924.90 6 7 Coefficients Standard Error t Stat P-value 8 Intercept 6.1092 0.9361 9 Usage 0.8951 0.149 10 11 12 13 14 15 16 17 18 19


Extracted 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 ANOVA df Ss MS F Significance F Regression 1. 1575.76 Residual 8 349.14 Total 1924.90 Coefficients Standard Error t Stat P-value Intercept 6.1092 0.9361 Usage 0.8951 0.149 If your answer is zero, enter "0". a. Write the estimated regression equation (to 4 decimals). b. Use a t test to determine whether monthly maintenance expense is related to usage at the 0.05 level of significance (to 2 decimals). Use Table 2 of Appendix B. t = p-value = Reject v the null hypothesis. Monthly maintenance expense is not v related to usage. c. Did the estimated regression equation provide a good fit? Explain. Hint: If p2 is greater than 0.50, the estimated regression equation provides a good fit. , because the value of pl is less v than 0.50. No