Pilot Shop is a catalog business providing a wide variety of aviation products to pilots throughout the world. Maynard Shephard, the recently hired assistant controller, has been asked to develop a cost function to forecast shipping costs. The previous assistant controller had forecast shipping department costs each year by plotting cost data against direct labor hours for the most recent 12 months and visually fitting a straight line through the points. The results were not satisfactory. After discussions with the shipping department personnel, Maynard decided that shipping costs could be more closely related to the number of cartons shipped. He based his conclusion on the fact that 10 months ago, the shipping department added some automated equipment. Furthermore, he believes that using linear regression analysis will improve the forecasts of shipping costs. Cost data for the shipping department have been accumulated for the last 25 weeks. He ran two regression analyses of the data, one using direct labor hours, and one using the number of cartons shipped. The information from the two linear regressions follows: Regression 1 Regression 2 SC 804.3+ 15.68DL SC 642.9 +3.92NCS 8.729 18.84 3.46 0.365 26.52 1.89 Equation R-squared Standard error of the estimate t-value where SC Total shipping department costs DL - Total direct labor hours NCS = Number of cartons shipped Required: 1. Identify which cost function (regression 1 or regression 2) Pilot Shop should adopt for forecasting total shipping department costs. 2. If Pilot Shop projects that 600 cartons will be shipped in the coming week, calculate the total shipping department costs using the regression you selected in requirement 1.