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\fDLL ' jx A A | B | C D E F G H I J 1 Production Volume (units) Total Cost ($) After reading these instructions delete all text in this shaded area. 2 400 4300 3 450 5300 Use the XLMiner Analysis ToolPak to conduct your regression analysis. 4 550 5700 5 600 6200 After deleting all text in this shaded area, set the output range in the ToolPak to the top left cell of this area (D1). 6 700 6700 7 750 7300 Your regression output should t into this shaded area. 8 9 10 Production Target Est. Cost ($) 11 500 12 13 14 15 16 17 18 19 3? Cost Estimation An important application of regression analysis in accounting is in the estimation of cost. By collecting data on volume and cost and using the least squares method to develop an estimated regression equation relating volume and cost, an accountant can estimate the cost associated with a particular manufacturing volume. In the Microsoft Excel Online le below you will nd a sample of production volumes and total cost data for a manufacturing operation. Conduct a regression analysis to explore the relationship between total cost and production volume and then answer the questions that follow. XE a. Compute b1 and ho (to 1 decimal). b1 b0 Complete the estimated regression equation (to 1 decimal). &=:|+|:lx b. According to this model, what is the change in cost (in dollars) for every unit produced (to 1 decimal)? c. Compute the coefcient of determination (to 3 decimals). Note: report r2 between 0 and 1. 3-: What percentage of the variation in total cost can be explained by the production volume (to 1 decimal)