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Table 1. Luke Corporation produces a variety of products, each within their own division. Last year, the managers at Luke developed and began marketing

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Table 1. Luke Corporation produces a variety of products, each within their own division. Last year, the managers at Luke developed and began marketing a new chewing gum, Bubbs, to sell in vending machines. The product, which sells for $5.25 per case, has not had the market success that managers expected, and the company is considering dropping Bubbs. Additional Information: 1. The product-line income statement for the past 12 months is shown in Table 1. 2. All products at Luke receive an allocation of corporate overhead costs, which is computed as 5 percent of the product's gross revenue. The 5 percent rate is based on the most recent year's corporate costs divided by corporate revenues. Data on corporate costs and revenues for the past two years are shown in Table 2. You may assume the fixed corporate overhead is $1,454,000 in each year. None of these fixed costs are specifically traceable to Bubbs. 3. Roy O. Andre, the product manager for Bubbs, is concerned about whether the product will be dropped by the company and has employed you as a financial consultant to help with some analysis. In addition to the information given above, Mr. Andre provides you with the data in Table 3 on the Bubbs monthly product costs. 4. Table 4 presents the results of a regression analysis of the data in Table 3. Product Line Income Statement for Bubbs - 12 months Revenue Costs $14,682,150 Manufacturing costs $14,440,395 Allocated corporate costs 734,108 Product-line margin Allowance for tax (@20%) Product-line profit (loss) 15,174,503 ($492,353) 98,470 ($393,883) Table 2. Corporate Most recent year Previous year Revenues $106,750,000 $76,200,000 OH Costs $5,337,500 $4,221,000 Fixed Corporate OH is $1,454,000 in each year Table 3. Monthly Production and Production Costs Month Cases Table 4. Regression Analysis of Table 3 Monthly Production Data Regression Statistics Multiple R 0.962 R Square 0.925 Adjusted R Square 0.918 Standard Error 12,833.693 Observations 12.000 Coefficients Intercept Cases 613,850 2.5474 Standard Error t Stat P-value 53,525 11.47 0.0000 0.23 11.12 0.0000 Prod. Costs 1 207,000 $ 1,139,828 2 217,200 S 1,161,328 3 214,800 $ 1,169,981 4 228,000 $ 1,185,523 5 224,400 $ 1,187,827 6 237,000 S 1,208,673 7 220,200 $ 1,183,699 8 247,200 $ 1,226,774 9 238,800 $ 1,225,226 10 252,600 $ 1,287,325 11 250,200 $ 1,241,760 12 259,200 S 1,272,451

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