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
Equation SC=804.3+ 15.68DL SC=642.9+ 3.92NR
R-squared 0.365 0.729
Standard error of
estimate 2.652 1.844
t-value 1.89 3.46

where:
SC = total shipping department costs
DL = total direct labor-hours
NR= number of cartons shipped

Required:
a. Identify which cost function (regression 1 or regression 2) Pilot Shop should adopt for forecasting total shipping department costs and explain why.
b. If Pilot Shop projects that 600 orders will be filled the coming week, calculate the total shipping department costs using the regression you selected in requirement 1.
c. Explain two or three important limitations of the regression you selected in requirement 1, and identify one or two ways to address the limitations. Specifically include in your discussion the effect, if any, of the global nature of Pilot Shop's business.

Ido not understand this project overview agricultural commodities are bought and sold through the stock exchange. the price of commodities changes all the time. investors buy many agricultural commodities before they are ready for shipping. when an investor buys an agricultural commodity that is going to be ready in the future, they call this purchasing futures. this might be a future crop, meat that has not yet been processed, or another type of agricultural commodity. for this project, you will have to decide how to spend $10,000. research the new york stock exchange. find one or more agricultural commodities that you are interested in. remember, it may be listed as a future crop. instructions identify the agricultural commodities that you think have the best chance of going up in price. think about what is going on with supply and demand. decide how you will spend your money. you may purchase only agricultural commodities. check the market every day for a week. record the price of your commodity or commodities each day. you may buy or sell your commodities at any time during the week. you may sell your commodities and buy different ones. feel free to experiment with the $10,000 by buying and selling commodities, but make sure to keep a careful record of your activities. at the end of the week, you will write a report on your investments. this report should be structured to include this information: page 1: explain how the stock market works. page 2: list all commodities purchased. describe each in detail. discuss why you selected these commodities. remember, they must be agricultural. page 3: create a chart or graph to illustrate the price of your commodity or commodities over the week’s time. list all of your activity buying and selling. make sure you include prices and details. page 4: write a summary of your experience. describe what you might do differently if you were using actual money. propose potential reasons why the price of each commodity may go up or down.