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. Consider the following sample of production volumes and total cost data for a manufacturing operation. Excel file: data14-21.xls Production Volume (units) Total Cost (S) 400 450 4000 5000 5400 550 600 5900 6400 700 750 7000 . Compute bị and bo (to 2 decimals if necessary). b1 bo Complete the estimated regression equation (to 2 decimals if necessary).

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. Consider the following sample of production volumes and total cost data for a manufacturing operation. Excel file: data14-21.xls Production Volume (units) Total Cost (S) 400 450 4000 5000 5400 550 600 5900 6400 700 750 7000 . Compute bị and bo (to 2 decimals if necessary). b1 bo Complete the estimated regression equation (to 2 decimals if necessary).

Economics (MindTap Course List)

13th Edition

ISBN:9781337617383

Author:Roger A. Arnold

Publisher:Roger A. Arnold

Chapter21: Production And Costs

Section21.4: Costs Of Production: Total, Average, Marginal

Problem 1ST

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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. Consider the following sample of production volumes and total cost data for a manufacturing operation. Production Volume (units) Total Cost ($) 400 4,000 450 5,000 550 5,400 600 5,900 700 6,400 750 7,000 a. Use these data to develop an estimated regression equation that could be used to predict the total cost for a given production volume. Do not round intermediate calculations. Compute b1 and bo (to 1 decimal). bị bo Complete the estimated regression equation (to 1 decimal). Do not round intermediate calculations b. What is the variable cost per unit produced (to 2 decimal)? Do not round intermediate calculations 2$ c. Compute the coefficient of determination (to 3…
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