costacctg13_sm_ch10

# 4thecostestimatebythetwomethodswill

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Unformatted text preview: costs appear to be quite small. Slope of high­low line.The slope of the line appears to be reasonably steep indicating that, on average, maintenance costs in a quarter vary with machine­hours used. 3. Using the cost funct ion est imated in 1, predicted maintenance costs would be \$2 × 90,000 = \$180,000. Howard should budget \$180,000 in quarter 13 because the relat ionship between machine­ hours and maintenance costs in So lut ion 10­31 is economically plausible, has an excellent goodness o f fit, and indicates that an increase in machine­hours in a quarter causes maintenance costs to increase in the quarter. 10­32 (30min.) High­low method and regression analysis. 1. See Solut ion Exhibit 10­32. SOLUTION EXHIBIT 10­32 Plot, High­low Line, and Regressio n Line for Number of Customers per Week versus Weekly Total Costs for Happy Business Co llege Restaurant Weekly Total Costs \$25,000 \$20,000 \$15,000 \$10,000 \$5,000 \$0 0 200 400 600 800 1000 Number of Customers per Week Regression line High­low line 10­20 2. Number of Customers per week Highest observation of cost driver (Week 9) 925 Lowest obser vation of cost driver (Week 2) 745 Differ ence 180 Weekly total costs = a + b (number of customers per week) Weekly Total Costs \$20,305 16,597 \$ 3,708 Slope coefficient (b) = \$3,708 = \$20.60 per customer 180 Constant (a) = \$20,305 – (\$20.60 ´ 925) = \$1,250 = \$16,597 – (\$20.60 ´ 745) = \$1,250 Weekly total costs = \$1,250 + \$20.60 (number of customers per week) See high­low line in So lution Exhibit 10­32. 3. Solut ion Exhibit 10­32 presents the regressio n line. Economic Plausibility. The cost funct ion shows a posit ive econo mically plausible relat ionship between number of customers per week and weekly total restaurant costs. Number of customers is a plausible cost driver since both cost of food served and amount of time the waiters must work (and hence their wages) increase with the number of customers served. Goodness of fit. The regression line appears to fit t...
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## This note was uploaded on 10/11/2010 for the course ACCT 321 taught by Professor Cole during the Spring '10 term at University of Miami.

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