Kilpauk Corporation, located in London, Ontario, has gathered data on its overhead activities and associated costs for the past 12 months. Nancy Cruder, a member of the controller?s department, has convinced management that the purchasing department?s overhead costs can be better estimated and controlled if the fixed and variable components of each overhead activity are known. Nancy has identified two possible variables (activity bases) that influence costs: (1) number of purchase orders and (2) kilograms of materials purchased. She does not knowwhich activity base will be a better predictor of costs. Therefore, she decides to gather data over a one-year period (see below).

Required:

1. Using the high?low method, develop a cost formula for the purchasing department?s overhead costs using the number of purchase orders as the activity base. Repeat using kilograms of materials as the activity base.

2. Using the least-squares regression method, develop a cost formula for the purchasing department?s overhead costs using the number of purchase orders as the activity base. Repeat using kilograms of materials as the activity base. You may use Excel or another spreadsheet to compute the answer.

3. For the next two months, the company expects to issue 1,200 orders per month. However, it expects to buy 40,000 kilograms in the first month and 50,000 kilograms in the following month. Compute the estimated costs for each of the two months using all the cost formulas that you have developed in parts (1) and (2).

4. Comment on the differences in costs that you have estimated in part (3), above. Which of the two methods (high?low versus regression) would you prefer in developing a cost formula? Why? Which of the two activity bases would you prefer to use? Why?

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Month Number of Purchase Orders Kilograms of Materials Overhead Cost 30,000 1,000 $15,980 900 25,000 15,000 1,500 3 45,000 24,200 32,000 17,000 1,100 1,300 44,000 22,150 6. 1,100 28,000 18,000 1,600 55,000 25,500 1,400 8. 39,000 23,660 1,650 23,500 25,000 10 950 23,000 15,240 11 1,250 37,500 21,900 35,000 19,500 12 1,150