FShop sells fresh roses. At the start of the day, the owner buys fresh roses. The supplier charges $1 per rose if the order quantity is five or less. If the order is for more than five roses, the charge is $0.91 per rose. FShop can sell the roses at $1.95 each. Any roses remaining unsold at the end of the day are sold to a discount store at $0.45 each. Based on past data, the daily demand for fresh roses is estimated to be between 1 and 10 with equal probability. Given this information, we need to decide as to how many roses FShop should buy at the start of each day. Use Excel spreadsheet to analyze the problem. Once again, your boss is allergic to mathematical equations. Base your conclusion by mimicking or simulating for 30 days. (hint: set up a table with columns as follows: day#, demand, profit with 1 in stock, profit with 2 in stock….. profits with 10 in stock. Demand for each day can be mimicked by entering =randbetween(1, 10) in some unused area of the spreadsheet, copy it down 29 rows. Then copy these 30 cells to clipboard, and paste them under “demand” column in your table. This method mimics the demand. When you paste them, do not use “paste”, but use “paste special” function to paste only the values).

Quantity5 or lessMore than 5Selling priceScrap Value Demand Cost Quantity06 Cumulativeprobability 52238431072539110659545552541155 Demand0.…

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