After a few hours May’s computer is fixed. May 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 May obtains is as follows: y = $2,582.6 + 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?
Extracted text: May Blackwell is the new manager of the materials storeroom for Clayton Manufacturing. May has been asked to estimate future monthly purchase costs for part #696, used in two of Clayton's products. May has purchase cost and quantity data for the past 9 months as follows: Quantity Purchased 2,710 parts 2,810 4,153 3,756 2,912 3,387 3,622 2,298 3,562 Cost of Purchase $12,675 Month January February 13,000 17,653 15,825 13,125 13,814 15,300 10,233 14,950 March April May June July August September Estimated monthly purchases for this part based on expected demand of the two products for the rest of the year are as follows: Purchase Quantity Expected 3,340 parts 3,710 3,040 Month October November December