1032 30min highlowmethodandregressionanalysis 1

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Unformatted text preview: oducing 2 Units 4 Units $388,000 $746,760 376,000 708,800 $ 12,000 $ 37,960 Total variable costs for manufacturing 2 and 4 units are lower under the cumulat ive average­t ime learning curve relat ive to the incremental unit­t ime learning curve. Direct manufacturing labor­hours required to make addit ional unit s decline more slowly in the incremental unit­time learning curve relat ive to the cumulat ive average­time learning curve when the same 90% factor is used for both curves. The reason is that, in the incremental unit­time learning curve, as the number of unit s double only the last unit produced has a cost of 90% of the init ial cost. In the cumulative average­time learning model, doubling the number o f unit s causes the average cost of all the addit ional units produced (not just the last unit) to be 90% of the init ia l cost. 10­18 10­31 (25 min.) High­low method. 1. Highest observat ion of cost driver Lowest observat ion of cost driver Difference Machine­Hours 125,000 85,000 40,000 Maintenance Costs $250,000 170,000 $ 80,000 Maintenance costs = a + b ´ Machine­hours Slope coefficient (b) = Constant (a) $80,000 = $2 per machine­hour 40,000 = $250,000 – ($2 × 125,000) = $250,000 – $250,000 = $0 o r Constant (a) = $170,000 – ($2 × 85,000) = $170,000 – $170,000 = $0 Maintenance costs = $2 × Machine­hours 2. SOLUTION EXHIBIT 10­31 Plot and High­Low Line of Machine­Hours on Maintenance Costs $260,000 240,000 M aintenance Costs 220,000 200,000 180,000 160,000 140,000 120,000 100,000 80,000 90,000 100,000 110,000 120,000 130,000 Machine­Hours 10­19 Solution Exhibit 10­31 presents the high­low line. Economic plausibility.The cost funct ion shows a posit ive econo mically plausible relat ionship between machine­hours and maintenance costs. There is a clear­cut engineering relat ionship o f higher machine­hours and maintenance costs. Goodness of fit.The high­low line appears to “fit” the data well. The vert ical differences between the actual and predicted...
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