Billy Bragg, marketing analyst of Green Mountain Sports, has decided to use A/F ratios for ordering decisions. Billy is trying to determine the order size for the standard hiking boot. A pair of standard boot sells for $55 and, due to a competitive supplier market, can be purchased for $30. The boots do not go out of style, but do cost $2.50 to hold a pair over from one season to the next (i.e., holding cost can be a proxy for the cost of overage). Green Mountain anticipates that the $55 price and $30 cost will remain the same for the next season. Bragg collected data from 20 items that he felt had market behavior similar to the standard boot. His forecast for the upcoming season is that demand will be 1000 boots. Using the data shown below and the price/cost information above, what is the profit maximizing order amount for the standard boot? (Hint: This can still be treated as a newsvendor model question. Use the empirical distribution when you do the A/F ratio analysis. Do not assume normality.) Product Num 1 Actual Demand Forecast A/F Ratio 2512 2041 1.23 2 1003 916 1.09 3 32 264 0.12 4 829 1471 0.56 5 95 1946 0.05 6 2122 1184 1.79 7 165 418 0.39 8 769 1514 0.51 9 1120 595 1.88 10 762 872 0.87 11 1317 1667 0.79 12 366 1216 0.30 13 1009 1266 0.80 14 1501 778 1.93 15 1918 1599 1.20 16 2306 2042 1.13 17 2058 1170 1.76 18 794 1607 0.49 19 552 323 1.71 20 638 801 0.80