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:...


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<br>brand of computer terminal.<br>Excel File: data14-41.xlsx<br>ANOVA<br>df<br>SS<br>MS<br>F<br>Significance F<br>Regression<br>1575.76<br>Residual<br>8<br>349.14<br>Total<br>1924.90<br>Coefficients Standard Error<br>t Stat<br>P-value<br>Intercept<br>6.1092<br>0.9361<br>Usage<br>0.8951<br>0.149<br>If your answer is zero, enter

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 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). ŷ = 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 В. t = p-value - Select your answer v the null hypothesis. Monthly maintenance expense Select your answer - related to usage. c. Did the estimated regression equation provide a good fit? Explain. Hint: If r is greater than 0.50, the estimated regression equation provides a good fit. - Select your answer - V because the value of r2 is - Select your answer - v than 0.50.

Jun 02, 2022
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