0151 JoAnne The Analysis of Mixed Costs Mixed costs are very

01:51 Jo-Anne The Analysis of Mixed Costs Mixed costs are very common. For example, the overall cost of providing X-ray services to patients at the Harvard Medical School Hospital is a mixed cost. The costs of equipment deprociation and radiologists\' and technicians\' salaries are fixed, but the costs of X-ray film, power, and supplies are variable. At Southwest Airlines, maintenance costs are a mixed cost. The company incurs fixed costs for renting maintenance facilities and for keeping skilled mechanics on the payroll, but the costs of replacement parts, ale 32 lubricating oils, tires, and so forth, are variable with respect to how often and how far the company\'s aircraft are flown The fixed portion of a mixed cost represents the minimum cost of having a service ready and available for use. The variable portion represents the cost incurred for actual consumption of the service, thus it varies in proportion to the amount of service actually consumed Managers can use a variety of methods to estimate the fixed and variable components of a mixed cost such as account analysis, the engineering approach, the high-low method, and least-squares regression analysis. In account analysis, an account is classifled as either variable or fixed based on the analyst\'s prior knowledge of how the cost in the account behaves. For example, direct materials would be classified as variable and a building lease cost would be classified as fixed because of the nature of those costs. The engineering approach to cost analysis involves a detailed analysis of what cost behavior should be, based on an industrial engineers evaluation of the production methods to be used, the materials specifications, labor requirements, equipment usage, production efficiency, power consumption, and so on. The high-low and least-squares regression methods estimate the fixed and variable elements of a mixed cost by analyzing past records of cost and activity data. We will use an example from Brentline Hospital to illustrate the high-low method caleulations and to compare the resulting high-low method cost estimates to those obtained using least-squares regression. Appendix 2A demonstrates how to use Microsoft Excel to perform least-squares regression computations Diagnosing Cost Behavior with a Scattergraph Plot LO2-5 Analyze a mixed cost using a scattergraph plot and the high-low method Assume that Brentline Hospital is interested in predicting future monthly maintenance costs for budgeting purposes. The senior management team believes that maintenance cost is a mixed cost and that the variable portion of this cost is driven by the number of patient-days. Each day a patient is in the hospital counts as one patient-day. The hospital\'s chief financial officer gathered the following data for the most recent seven-month period: ut

Solution

Brentline Hospital

8500

X axis

	Month	Patient days	Maintenance Cost
	Jan	5600	7900				Scattergraph
	Feb	7100	8500 Scattergraph I could create the scattergraph in Excel but I could not paste it here Patient Days X axis Patient days (X axis)	Scattergraph Patient Days X axis Patient days (X axis)
	Mar	5000	7400
	Apr	6500	8200
	May	7300	9100
	Jun	8000	9800
	Jul	6200	7800
						Patient Days	X axis
							Patient days (X axis)
			The first step in applying the high-low method or the least squares regression method is to diagnose cost behaviour with a scattergraph plot. The scattergraph plot of maintenance cost versus patient-days at Brentline Hospital is shown in Exhibit 2-6. Two things should be noted about this scattergraph. 1 The total maintenance, Y, is plotted on the vertical axis. Cost is known as the dependent variable because the amount of cost incurred during a period depends on the level of activity for the period. (That is, as the level of activity increases the cost will also increase Month Patient days Maintenance Cost Jan 5600 7900 Scattergraph Feb 7100 8500 Mar 5000 7400 Apr 6500 8200 May 7300 9100 Jun 8000 9800 Jul 6200 7800 Patient Days X axis Patient days (X axis)