### Conduct a multiple regression of overhead

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##### Reference no: EM13341432

Cost Estimation

The CEO of Milton Manufacturing Company has asked you to develop a cost equation to predict monthly overhead costs in its production department. You have collected the following data for the last 10 months: Overhead costs (OH\$) and the proposed independent variables: Number of machine hours worked (MH), number of direct labour hours (DLH) and number of indirect labour workers (IL Workers).

 OH (\$) MH DLH IL Workers 2,000 9,500 1,800 3 4,500 20,000 4,200 8 3,000 14,000 2,500 15 2,700 13,000 2,400 10 6,000 28,000 5,000 16 5,100 25,000 4,800 12 8,000 42,000 8,100 6 4,800 25,000 4,500 8 7,500 35,000 6,900 14 6,500 32,000 6,000 11

(a) The CEO suggests that he has heard that the high-low method of estimating costs works fairly well and should be inexpensive to use. Write a response to this suggestion for the CEO indicating the advantages and disadvantages, including the calculation of a cost equation for this data using MH as the cost driver.

(b) Using Excel develop three scatter diagrams showing overhead costs against each of the proposed independent variables. Comment on whether these scatter diagrams indicate that linearity is a reasonable assumption for each.

(c) Using the regression module of Excel's Add-in Data Analysis, perform 3 simple regressions by regressing overhead costs against each of the proposed independent variables. Evaluate each of the regression results, indicating which is best and why. Provide the cost equations for those regression results which are satisfactory and from them calculate the predicted overhead in a month where there were 10,000 MH and 3,000 DLH worked.

(d) Selecting the two best regressions from part (c) conduct a multiple regression of overhead against these two independent variables. Evaluate the regression results. If there should be a problem identify the problem and draw conclusions about the best of the four regression results to use.

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