methods (Learning Objectives 1, 2, 3, 4, & 5) Sandy Dawson is the Chief Operating Officer at Mercy Hospital in Atlanta, Georgia. She is analyzing the hospital's overhead costs but is not sure whether nursing hours or the number of patient days would be the best cost driver to use for predicting the hospital's overhead. She has gathered the following information for the last six months of the most recent year: Hospital Number Overhead Overhead Overhead Nursing of Patient Cost per Cost per Month Costs Hours Days Nursing Hour Patient Day July....................001 $483,000 24,500 3,790 $19.71 $127.44 August................... $535,000 28,500 4,310 $18.77 $124.13 September $411,000 19,500 4,230 $21.08 $ 97.16 October $451,000 20,500 3,450 $22.00 $130.72 November $576,000 32,000 5,710 $18.00 $ 100.88 December........ $446,000 20,000 3,290 $22.30 $135.56 Requirements 1. Are the hospital's overhead costs fixed, variable, or mixed? Explain. 2. Graph the hospital's overhead costs against nursing hours. Use Excel or graph by hand. 3. Graph the hospital's overhead costs against the number of patient days. Use Excel or graph by hand. 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 25,500 nursing hours are pre- dicted for the month. HAPTER 6 6. Dawson 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: SUMMARY OUTPUT-Nursing hours as cost driver 2 Regression Statistics 3 Multiple R 0.984685 4R Square 2 0.969605 6 Standard Error 7 Observations R 2 ANOVA 10 Regression 11 Residual 5 Adjusted R Square 0.962006 11.992.70481 df SS M5 118,352 033,459 18.352.0)8,459 4 525 299,875 127.599774 Significance F 000015 143824969 Total 5 18,877333,334 11 3 16 Standard LOWET 22 15 Coefficients Stat 16 Intercept 19960979 25,618 85 17 X Variable 1 11.75 1.041 7.792 11.296 Pralue 0.001 0.000 Upper 95% 128,480456| 270,739.118 8.365 14643 18 If 25,500 nursing hours are predicted for the month, what is the total predicted hospi- tal overhead? 7. Dawson then ran the regression analysis using number of patient days as the cost driver. The Excel output from the regression is shown here: 1 SUMMARY OUTPUT-Using number of patient days as cost driver Regression Statistics 3 Mutiple R 4R Square 5 Adjusted R Square 6 Standard Error 7 Observations 8ANOVA 9 10 Regression 11 Residual 12 Total 0.750775 0.563662 0.454578 45,438.70968 of MS 1 10,668,627,982 10,668.627,982 || 5.167216 4 8,258,705,351 2,064,676,338 5 18,927,333,333 16 Intercept Coeficients 265,475.95 Standard Emor 97,762.101 17 X Variable 1 52.83 23.241 10057 Significance F 008543 Lower P-value 95% Upper 95% 2.176 0.053 2.273 0.085 -11.697 5,955.158 536,907.056 117.359 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