After assembling a dataset that includes your employer's, the Yay Company's, sales history and some relevant variables that might help predict sales, you ran a regression and arrived at the following forecast model: Q = 10,000 - 0.7P - 0.25PM - I, where Q is Yay's yearly sales, P is Yay's price, PM is the Meh Company's price, and I is the average annual consumer income after tax. Your boss is specifically interested in how sales depend on Yay's price. You explain that this information would be captured by a standard demand function. A review of the current price of the Meh Company and current consumer incomes shows that PM = 400 and 1= 2,900. You inform your boss that the demand function is: Q = 2,900 +0.25PM Q = 3,000 - 0.95P Q = 6,600 +0.25PM Q = 7,000 -0.7P
