I got wrong for these REQUIREMENT 3(Numbers stated in the box with red mark on the right corner are correct answers that the website showed me, but I don't know how to determine those answers). Also, I don't know how to determine for those blank box of REQUIREMENT 4. So please provide calculations for REQUIREMENT 3 and 4 to determine those answers.
Marie Bly is the new manager of the materials storeroom for Starr Manufacturing. Marie has been asked to estimate future monthly purchase costs for part #696, used in two of Starr's products. Marie has purchase cost and quantity data for the past 9 months as follows: :: (Click the icon to view the data for the past 9 months.) Estimated monthly purchases for this part based on expected demand of the two products for the rest of the year are as follows: (Click the icon to view the expected demand for the rest of the year.) Read the requirements. Requirement 3. After a few hours Marie's computer is fixed. Marie 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 Marie obtains is as follows: y = $2,223.2 + 3.66X Run a regression on the 9 months of data using Microsoft Excel to determine R Square andt Stat for the X Variable 1 statistics. (Enter the R Square and t Stat amounts to six decimal places, O.XXXXXX.) Regression Statistics R Square 0.973516 t Stat X Variable 1 16.040989 Requirement 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. Begin by using the regression results to calculate the expected purchase costs for October, November, and December. (Use amounts as given in the information to two decimal places. Do not round interim calculations, but then do round your final answers [expected cost amounts) to the nearest whole dollar.) Regression Equation Expected Cost Month Purchase Quantity Expected October 3,340 parts 3,740 parts November December 3,030 parts X i Data Table Data Table $ Month January February March April May Cost of Purchase $ 12,675 12,770 17,507 16,099 13,000 14,012 15,237 Quantity Purchased 2,680 parts 2,820 4,101 3,777 2,945 3,376 3,600 2,253 3,512 June July August September 10,115 15,000 X ata Table Data Table Month October November December Purchase Quantity Expected 3,340 parts 3,740 3,030 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 Marie's computer is fixed. Marie 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 Marie obtains is as follows: y = $2,223.2 + 3.66X 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
