Question

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

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, or​ mixed? 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 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 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:

Regression analysis using number of patient days

SUMMARY OUTPUT​ - Using number of patient days as 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 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.

Answer 1

1) The hospital's overhead costs appear to be a Mixed cost. If it were afixed cost, it would remain constant in total each month. If it were a 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 vary with volume