One way retail industry uses machine learning is to predict how much quantity Q of some product they should buy to maximize their profit. The optimal quantity depends on how much demand D there is for the product, as well as its cost for the retailer to buy C, and its selling price P to the customer. Assuming that the demand D is distributed as P(D), we can evaluate the expected profit considering two cases