High-low, regression. 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:
Estimated monthly purchases for this part based on expected demand of the two products for the rest of the year are as follows:
1. The computer in May’s office is down, and May has been asked to immediately provide an equation to estimate the future purchase cost for part #696. May 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 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:
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
2. Comment on your results.
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