Fundamentals of Cost Accounting 3rd Edition by William N. Lanen, Shannon W. Anderson, Michael Maher

Exercise 48

Cost Estimation: Simple Regression

The following information on maintenance and repair costs and revenues for the last two years is available from the accounting records at Arnie’s Arcade&Video Palace. Arnie has asked you to help him understand the relation between business volume and maintenance and repair cost.

Month	Maintenance and Repair Cost	Revenues
	($000)	($000)
July	$1.56	$ 44
August	2.53	38
September	2.05	34
October	1.46	50
November	1.55	62
December	0.39	90
January	2.37	30
February	2.41	36
March	2.27	46
April	2.23	48
May	1.29	52
June	1.03	64
July	1.85	58
August	1.27	52
September	1.82	60
October	1.63	62
November	0.68	72
December	0.01	102
January	1.83	46
February	1.53	48
March	0.94	68
April	1.20	72
May	1.20	58
June	1.78	54

Required

a. Ignoring the data, would you predict that, in general, there is a positive relation between revenues and maintenance and repair costs? Why?

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b. Estimate a linear regression with maintenance and repair cost as the dependent variable and revenue as the independent variable. Does the result support your prediction in part (a)? What are some factors that may explain the result?

Step 1 of 3

Cost estimation

Cost estimation is an important exercise because it helps managers in decision making. Correct cost estimates result in cost saving and making business successful. Cost estimates helps managers to evaluate and choose the best alternative. It is important for managers to capture the correct cost for each alternative.

There different methods used for cost estimation like engineering, accounting and statistical analysis.

Statistical method

Statistical is more accurate method of cost estimation as compared to engineering and accounting analysis method as they have certain limitations. Under this method, random events are separated from while analyzing relationship between cost and activity. While using statistical method for cost estimation it is important to confirm that past activity levels are related to current estimation.

Simple regression analysis – In simple regression analysis there is only one predictor for the activity and cost is estimated on the basis on one predictor only. For example, overhead cost is estimated on the basis of relationship between total cost and parts used.

Multiple regression analysis – In multiple regression analysis more than one type of predictor is used for the activity and cost is estimated on the basis on multiple predictors. Multiple predictors are used for better and more accurate cost estimation. For example, overhead cost is estimated on the basis of parts used and labor hours used for production purpose. Only parts cost may not provide correct overhead cost estimation, hence labor hours used, must also be included as predictor to calculate overhead cost.