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Using "Excel" do the following problem using "the High-Low Method" and "Regression Analysis" and turn in the Excel file including your recommendations. Feel free to ask any questions concerning this project. You can discuss this project with other classmates, but do not copy somebody else's outputs. Remember the due date. *To run the regression using the Excel Program, use Tools, Data Analysis, Regression and choose x - cost driver and y -costs we want to predict. If you use regression for the first time, click File, Options, in left column then click Add-ins, Analysis toolpak, Regression just for setting up the regression program once. If you use Apple or Mac computer, there are instructions in Blackboard how to run regression analysis. Problem: The King Corporation is developing a model to explain and predict overhead costs. It produces only one product-line so that a simple count of the number of units produced each month may be a good measure of activity to begin with. The company has collected data for the past twelve months: Month Overhead Production Cost Units 1 2 3 4 5 6 7 8 9 $254,500 184,500 165, 400 178,000 192,000 225,000 210,000 230,000 195,000 224,000 200,000 240,000 40,000 24,000 21,000 23,000 25,000 31,000 28,000 30,000 29,000 36,000 32,000 38,000 10 - 11 12 Required: 1. Open a spreadsheet and enter the data. Required: 1. Open a spreadsheet and enter the data. 2. Create another worksheet and enter High-Low method formula to calculate variable cost per unit and total fixed costs. Use y = a + b(x) formula. Enter a (total fixed costs) in Cell 20B and b (variable cost per unit) in Cell 200. 3. Create another worksheet and run regression (Least Squared Method) and save the output. 4. Create another worksheet and save both outputs by linking worksheets. Determine whether the High-Low method or Regression Analysis is better to predict monthly overhead costs. Explain which model is the better? Why or why not? 5. Use the results of your regression analysis in the y = a + b(x) formula to predict overhead costs for January and December of next year. Use a 12-month average of your current year production units for the projection for both months. Do you think these predicted overhead costs are reasonable? (Refer to our textbook from pp. 221-223 for regression analysis details.)