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 $5.50 per case, has not had the market success that managers expected, and the company is considering dropping Bubbs. The product-line income statement for the last month follows: Revenue Costs Production costs Product-line margin Allowance for tax (@20%) Product-line profit (loss) Month Cases 220,500 219,200 3 216,900 4 233,000 1 2 5 238,100 6 241,400 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, Mr. Andre provides you with the following data on production costs for Bubbs for the past 12 months: 7 222,200 8 249,200 9 243,200 10 254,600 $ 11 249,500 12 257,450 $ 1,415,975 (1,255,451) 160,524 (32,104.80) 128,419.20 Production Costs $1,155,250 1,174,265 1,172,918 1,191,523 1,195,827 1,216,673 1,195,699 1,215,210 1,233,226 1,250,377 1,249,760 1,255,451 Assume that the relevant range of production is between 150,000 and 275,000 cases. How many cases of Bubbs does Luke have to sell in a single month in order to break even on the product? Use Regression in Excel to find the fixed and variable portions of the production costs. o Cases will be the X variable and Production Costs will be the Y variable. o Produce a line-fit plot with the regression output and with axes correctly labeled.