A sweatshirt supplier is trying to decide how many sweatshirts to print for the upcoming NCAA basketball championships. The final four teams have emerged from the quarterfinal round, and there is now a week left until the semifinals, which are then followed in a couple of days by the finals. Each sweatshirt costs $10 to produce and sells for $25. However, in three weeks, any leftover sweatshirts will be put on sale for half price, $12.50. The supplier assumes that the demand for his sweatshirts during the next three weeks (when interest in the tournament is at its highest) has the distribution shown in the file P15_14.xlsx. The residual demand, after the sweatshirts have been put on sale, has the distribution also shown in this file. The supplier, being a profit maximizer, realizes that every sweatshirt sold, even at the sale price, yields a profit. However, he also realizes that any sweatshirts produced but not sold (even at the sale price) must be thrown away, resulting in a $10 loss per sweatshirt. Use @RISK to analyze the sweatshirt situation. Using the discrete distributions given in the problem, what are the mean and the standard deviation of the profit to the sweatshirt supplier should he decide to print 11,000 sweatshirts? Round your answers to the nearest whole dollar, if necessary.

Demand distribution at regular price Demand distribution at reduced price Demand Probability Demand Probability 7 0.05 2 0.20 8 0.10 3 0.30 Note: All demands shown 9 0.25 4 0.20 are in 1000s of sweatshirts. 10 0.30 5 0.15 11 0.20 0.10 12 0.10 0.05