Molly O'Malley is the new manager of the materials storeroom for Tudor Manufacturing. Mollly has been asked to estimate future monthly purchase costs for part #696, used in two of Tudor's products. Molly has purchase cost and quantity data for the past 9 months as follows:

Month	Cost of Purchase	Quantity Purchased
January	$12,410	2,650 parts
February	12,770	2,850
March	17,403	4,116
April	15,838	3,761
May	13,249	2,901
June	14,022	3,376
July	15,237	3,644
August	10,087	2,287
September	14,900	3,592

Estimated monthly purchases for this part based on expected demand of the two products for the rest of the year are as follows:

Month	Purchase Quantity Expected
October	3,350 parts
November	3,770
December	3,050

The computer in Molly's office is down, and Molly has been asked to immediately provide an equation to estimate the future purchase cost for part #696. Molly grabs a calculator and uses the high-low method to estimate a cost equation. What equation does she get?

2. Using the equation from requirement 1, calculate the future expected purchase costs for each of the last 3 months of the year.

3. After a few hours Molly's computer is fixed. Molly uses the first 9 months of data and regression analysis to estimate the relationship between the quantity purchased and purchase costs of part #696. The regression line Mollyobtains is as follows:

y = $2,505.3 + 3.54X

Evaluate the regression line using the criteria of economic plausibility, goodness of fit, and significance of the independent variable. Compare the regression equation to the equation based on the high-low method. Which is a better fit? Why?

4. Use the regression results to calculate the expected purchase costs for October, November, and December. Compare the expected purchase costs to the expected purchase costs calculated using the high-low method in requirement. Comment on your results.