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The manager of the main laboratory facility at Capital Health Center is interested in being able to predict the overhead costs The laboratory manager performed

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The manager of the main laboratory facility at Capital Health Center is interested in being able to predict the overhead costs The laboratory manager performed a regression analysis to predict total laboratory overhead costs. The output generated by each month for the lab. The manager believes that total overhead varies with the number of lab tests performed but that some Excel is as follows: costs remain the same each month regardless of the number of lab tests performed. The lab manager collected the following Click the icon to view the completed regression analysis.) data for the first seven months of the year. (Click the icon to view the data.) Read the requir Requirements Requirement 1. Determine the lab's cost equation (use the output from the Excel regression). (Round the amounts to two decimal places.) y = 1. Determine the lab's cost equation (use the output from the Excel regression) 2. Determine the R-squared (use the output from the Excel regression). 3. Predict the total laboratory overhead for the month if 3,000 tests are performed. Data Table Data Table Print Done Number of Lab Tests Performed B D E F G Month Total Laboratory Overhead Costs $28,900 1 SUMMARY OUTPUT 3.300 2 Regression Statistics 3,150 January February .... March April May ...... $28,300 $32,500 3 Multiple R 4,100 4.250 0.94799 0.898685 $ 34,000 4 R Square 5 Adjusted R Square 4,500 0.878422 June ...... 1,500 $29,900 $ 17,000 $15.500 6 Standard Error 2562.300148 July ..... 1,700 7 7 Observations BANOVA of MS Print SS F Done 9 10 Regression 11 Residual Significance F 0.001152 1 291181661.19 291181661.19 44.351061 5 32826910.24 6565382.048 12 Total 6 324008571.43 13 Stat P-value Lower 95% Coefficients 8047.25 Standard Error 2947.351 Upper 95% 15623.652 14 Intercept 0.041 2.730 6.660 470.840 3.541 15 X Variable 1 5.77 0.866 Enter any number in the edit fields and then click Check 0.001 7.994

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