Jaden Kyler is the Chief Operating Officer at United Hospital in Newark New Jersey. He is analyzing thehospital'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.

He has gathered the following information for the last six months of the most recent year:

Data Table:

	Hospital	Nursing	Number of	Overhead Cost	Overhead Cost
Month	Overhead Costs	Hours	Patient Days	per Nursing Hour	per Patient Day
July. . . . . . .	$479,000	23,000	3,640	$20.83	$131.59
August. . . .	$528,000	25,500	4,300	$20.71	$122.79
September.	$416,000	20,500	4,260	$20.29	$97.65
October. . . .	$453,000	22,000	3,490	$20.59	$129.80
November. .	$559,000	30,500	5,730	$18.33	$97.56
December.	$435,000	21,000	3,280	$20.71	$132.62

Requirements:

1. Are the hospital's overhead costs fixed, variable, ormixed? Explain.

The hospital's overhead costs appear to be a ▼(fixed, mixed, variable cost). If it were a ▼ (fixed, mixed, variable cost), it would remain constant in total each month. If it were a ▼ (fixed, mixed, variable cost), it would remain constant on a per unit (of activity) basis. Both of the hospital's overhead cost per nursing hour and overhead cost per patient day ▼ (are fixed, vary) with volume.

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 24,500 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:

Regression analysis using nursing hours

SUMMARY OUTPUT - Nursing hours as a cost driver

Regression Statistics
Multiple R		0.958335
R Square		0.918405
Adjusted R Square		0.898007
Standard Error		17,712.08289
Observations		6

ANOVA
	df	SS	MS	F	Significance F
Regression	1	14,124,461,812	14,124,461,812	45.022814	0.002568
Residual	4	1,254,871,522	313,717,880
Total	5	15,379,333,334

		Standard			Lower	Upper
	Coefficients	Error	t Stat	P-value	95%	95%
Intercept	141,867.97	50,663.259	2.8	0.049	1,204.213	282,531.726
X Variable 1	14.17	2.111	6.71	0.000	8.305	20.029

If 24,500 nursing hours are predicted for the month, what is the total predicted hospitaloverhead?

7. Kyler then ran the regression analysis using a number of patient days as the cost driver. The Excel output from the regression is shown here:

Regression analysis using a number of patient days

SUMMARY OUTPUT - Using a number of patient days as a cost driver

Regression Statistics
Multiple R		0.736429
R Square		0.542327
Adjusted R Square		0.427909
Standard Error		41,948.4953
Observations		6

ANOVA
	df	SS	MS	F	Significance F
Regression	1	8,340,628,301	8,340,628,301	4.739865	0.09505
Residual	4	7,038,705,032	1,759,676,258
Total	5	15,379,333,333

		Standard			Lower	Upper
	Coefficients	Error	t Stat	P-value	95%	95%
Intercept	289,807.47	88,271.2	3.283	0.03	44,727.331	534,887.615
X Variable 1	45.8	21.035	2.177	0.095	-12.607	104.198

If 3,650 patient days are predicted for the month, what is the total predicted hospitaloverhead?

8. Which regression analysis (using nursing hours or using a number of patient days as the cost driver) produces the best cost equation? Explain your answer.