1. Conduct a regression using the monthly data of operating costs on freight miles. You should obtain the

following result:

2. Plot the data and regression line for the above estimation. Evaluate the regression using the criteria of economic plausibility, goodness of fit, and slope of the regression line. 3. Brown expects Spirit to generate, on average, 3,600 freight miles each month next year. How much in operating costs should Brown budget for next year? 4. Name three variables, other than freight miles, that Brown might expect to be important cost drivers for Spirit?s operating costs. 5. Brown next conducts a regression using the monthly data of maintenance costs on freight miles. Verify that she obtained the following result:

6. Provide a reasoned explanation for the observed sign on the cost driver variable in the maintenance cost regression. What alternative data or alternative regression specifications would you like to use to better capture the above relationship?

NUMBER 2

1. Calculate predicted total costs of producing the six PT109s for the Navy. (Blue Seas will keep the first deployment boat assembled, costed at $1,533,900, as a demonstration model for potential customers.) 2. What is the dollar amount of the difference between (a) the predicted total costs for producing the six PT109s in requirement 1 and (b) the predicted total costs for producing the six PT109s, assuming that there is no learning curve for direct manufacturing labor? That is, for (b) assume a linear function for units produced and direct manufacturing labor-hours.