A chain of department stores is introducing a new brand of bathing suit for $70. The prime selling season is 50 days during the late spring and early summer; after that, the store has a clearance sale around July 4th and marks down the price by 70% (to $21.00), typically selling any remaining inventory at the clearance price. Merchandise buyers have purchased 1,000 units and allocated them to the stores prior to the selling season. After a few weeks, the stores reported an average sales of 7 units/day, and past experience suggests that this constant level of sales will continue over the remainder of the selling season. Thus, over the 50-day selling season, the stores would be expected to sell 50 7 = 350 units at the full retail price and earn a revenue of $70.00 350 = $24,500. The remaining 650 units would be sold at $21.00, for a clearance revenue of $13,650. Therefore, the total revenue would be predicted as $24,500 + $13,650 = $38,150. As an experiment, the store reduced the price to $49 for one weekend and found that the average daily sales were 32.2 units. Fit a linear trend model for sales as a function of price: daily sales = a b price A) Based on this model, confirm if higher sales can be driven by price discounts. B) If the model confirms the above relationship, the marketing department has the basis for making improved discounting decisions. For instance, suppose they decide to sell at full retail price for x days and then discount the price by y% for the remainder of the selling season, followed by the clearance sale. What total revenue could they predict? Build a spreadsheet model to calculate the total revenue