this is all one question Im sorry having a hard time with this question
Bailey Kyler is the Chief Operating Officer at Strong Hospital in Charleston, South Carolina. She is She has gathered the following information for the last six months of the most recent year analyzing the hospital's overhead costs but is not sure whether nursing hours or the number of Click the icon to view the information) patient days would be the best cost driver to use for predicting the hospital's overhead. Read the girements (Arter you continue the screen may take you below the beginning of the next stop. if so, scroll back up to the top of the step.) Requirement 2. Graph the hospital's overhead costs against nursing hours. Plot the points on the graph. (Enlarge the graph and use the point tool button displayed below to draw the graph) Relationship of Hospital Overhead Costs to Nursing Hours Hospital Overhead Costs 16 Oca 2.500 Nursing Hours Click to enlarge graph Click the graph, choose a tool in the palette and follow the instructions to create... V V o - --- Delete Hospital Overhead Costs Relationship of Hospital Overhead Costs to Nursing Hours $580,000 $570,000 $560,000 $550,000 $540,000 $530,000 $520,000 $510,000 $500,000 $490,000 $480,000 $470,000 $460,000 $450,000 $440,000 $430,000 $420,000 $410,000 $400,000 $390,000 16,000 18,500 21,000 23,500 26,000 28,500 31,000 33,500 Nursing Hours Clear ? Selected: none TE Save Cancel Data Table Hospital Overhead Costs Nursing Hours Month $ 462,000 22,900 Number of Overhead Cost Overhead Cost Patient Days per Nursing Hour per Patient Day 3,610 $ 20.17 $ 127.98 4,330 $ 19.39 $ 117.78 4,250 $ 22.91 $ 94.35 July August September October 30.00090 510,000 401,000 445,000 $ 26,300 17,500 21,700 30,000 19,000 3,460 $ 20.51 $ 128.61 November $ 5,740 $ 18.53 $ 96.86 Seles 556,000 430,000 December $ 3,230 $ 22.63 $ 133.13 none ol in the Print Done Clear All Che 0 Requirements X 1. Are the hospital's overhead costs fixed, variable, or mixed? Explain. 2. Graph the hospital's overhead costs against nursing hours. 3. Graph the hospital's overhead costs against the number of patient days. 4. Do the data appear to be sound or do you see any potential data problems? Explain. 5. Use the high-low method to determine the hospital's cost equation using nursing hours as the cost driver. Predict total overhead costs if 23,400 nursing hours are predicted for the month. 6. Kyler runs a regression analysis using nursing hours as the cost driver to predict total hospital overhead costs. The Excel output from the regression analysis is as follows: Click the icon to view the regression analysis.) If 23,400 nursing hours are predicted for the month, what is the total predicted hospital overhead? 7. Kyler then ran the regression analysis using number of patient days as the cost driver. The Excel output from the regression is shown here: E (Click the icon to view the regression analysis.) If 3,680 patient days are predicted for the month, what is the total predicted hospital overhead? 8. Which regression analysis (using nursing hours or using number of patient days as the cost driver) produces the best cost equation? Explain your answer. Regression analysis using nursing hours X SUMMARY OUTPUT - Nursing hours as cost driver Regression Statistics Multiple R 0.993809 R Square 0.987656 Adjusted R Square 0.984569 Standard Error 7,027.671539 Observations ANOVA 6 df SS MS F Significance F Regression Residual 15,805,780,664 320.031731 0.000057 4 15,805,780,664 197,552,669 16,003,333,333 49,388, 167 Total 5 Standard Lower Upper 95% Coefficients Error Star P-value 95% Intercept 190,017.69 12.053 0 146, 247.28 233,788.101 15,764.911 0.677 X Variable 1 12.11 17.889 0.000 10.23 13.989 SUMMARY OUTPUT - Using number of patient days as cost driver Regression Statistics Multiple R 0.753409 R Square 0.567626 Adjusted R Square 0.459532 Standard Error 41,591.55002 Observations 6 ANOVA dr SS MS F Significance F 5.251246 0.083713 Regression Residual 1 9,083,905,201 6,919,428,132 16,003,333,333 9,083,905.201 1,729,857,033 4 Total 5 Standard Lowor Upper Coefficients Error Stat P-value 95% 95% Intercept 275,852.53 85,266.887 3.235 0.032 39,113.7 512,591.364 X Variable 1 46.66 20.364 2.292 0.084 -9.874 103.203 Print Done Bailey Kyler is the Chief Operating Officer at Strong Hospital in Charleston, South Carolina. She is She has gathered the following information for the last six months of the most recent year analyzing the hospital's overhead costs but is not sure whether nursing hours or the number of Click the icon to view the information) patient days would be the best cost driver to use for predicting the hospital's overhead. Read the girements (Arter you continue the screen may take you below the beginning of the next stop. if so, scroll back up to the top of the step.) Requirement 2. Graph the hospital's overhead costs against nursing hours. Plot the points on the graph. (Enlarge the graph and use the point tool button displayed below to draw the graph) Relationship of Hospital Overhead Costs to Nursing Hours Hospital Overhead Costs 16 Oca 2.500 Nursing Hours Click to enlarge graph Click the graph, choose a tool in the palette and follow the instructions to create... V V o - --- Delete Hospital Overhead Costs Relationship of Hospital Overhead Costs to Nursing Hours $580,000 $570,000 $560,000 $550,000 $540,000 $530,000 $520,000 $510,000 $500,000 $490,000 $480,000 $470,000 $460,000 $450,000 $440,000 $430,000 $420,000 $410,000 $400,000 $390,000 16,000 18,500 21,000 23,500 26,000 28,500 31,000 33,500 Nursing Hours Clear ? Selected: none TE Save Cancel Data Table Hospital Overhead Costs Nursing Hours Month $ 462,000 22,900 Number of Overhead Cost Overhead Cost Patient Days per Nursing Hour per Patient Day 3,610 $ 20.17 $ 127.98 4,330 $ 19.39 $ 117.78 4,250 $ 22.91 $ 94.35 July August September October 30.00090 510,000 401,000 445,000 $ 26,300 17,500 21,700 30,000 19,000 3,460 $ 20.51 $ 128.61 November $ 5,740 $ 18.53 $ 96.86 Seles 556,000 430,000 December $ 3,230 $ 22.63 $ 133.13 none ol in the Print Done Clear All Che 0 Requirements X 1. Are the hospital's overhead costs fixed, variable, or mixed? Explain. 2. Graph the hospital's overhead costs against nursing hours. 3. Graph the hospital's overhead costs against the number of patient days. 4. Do the data appear to be sound or do you see any potential data problems? Explain. 5. Use the high-low method to determine the hospital's cost equation using nursing hours as the cost driver. Predict total overhead costs if 23,400 nursing hours are predicted for the month. 6. Kyler runs a regression analysis using nursing hours as the cost driver to predict total hospital overhead costs. The Excel output from the regression analysis is as follows: Click the icon to view the regression analysis.) If 23,400 nursing hours are predicted for the month, what is the total predicted hospital overhead? 7. Kyler then ran the regression analysis using number of patient days as the cost driver. The Excel output from the regression is shown here: E (Click the icon to view the regression analysis.) If 3,680 patient days are predicted for the month, what is the total predicted hospital overhead? 8. Which regression analysis (using nursing hours or using number of patient days as the cost driver) produces the best cost equation? Explain your answer. Regression analysis using nursing hours X SUMMARY OUTPUT - Nursing hours as cost driver Regression Statistics Multiple R 0.993809 R Square 0.987656 Adjusted R Square 0.984569 Standard Error 7,027.671539 Observations ANOVA 6 df SS MS F Significance F Regression Residual 15,805,780,664 320.031731 0.000057 4 15,805,780,664 197,552,669 16,003,333,333 49,388, 167 Total 5 Standard Lower Upper 95% Coefficients Error Star P-value 95% Intercept 190,017.69 12.053 0 146, 247.28 233,788.101 15,764.911 0.677 X Variable 1 12.11 17.889 0.000 10.23 13.989 SUMMARY OUTPUT - Using number of patient days as cost driver Regression Statistics Multiple R 0.753409 R Square 0.567626 Adjusted R Square 0.459532 Standard Error 41,591.55002 Observations 6 ANOVA dr SS MS F Significance F 5.251246 0.083713 Regression Residual 1 9,083,905,201 6,919,428,132 16,003,333,333 9,083,905.201 1,729,857,033 4 Total 5 Standard Lowor Upper Coefficients Error Stat P-value 95% 95% Intercept 275,852.53 85,266.887 3.235 0.032 39,113.7 512,591.364 X Variable 1 46.66 20.364 2.292 0.084 -9.874 103.203 Print Done
