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 4,500 450 5,500 550 5,900 600 6,400 700 6,900 750 7,500 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 b0 (to 1 decimal). Do not round intermediate calculations. Complete the estimated regression equation (to 1 decimal). Do not round intermediate calculations. y= + xb. What is the variable cost per unit produced (to 2 decimal)? Do not round intermediate calculations. $c. Compute the coefficient of determination (to 3 decimals). Do not round intermediate calculations. Note: report r^2 between 0 and 1 . What percentage of the variation in total cost can be explained by the production volume (to 1 decimal)? Do not round intermediate calculations. %d. The company's production schedule shows 500 units must be produced next month. Predict the total cost for this operation (to the nearest whole number). Do not round intermediate calculations.

Elementary Linear Algebra (MindTap Course List)

8th Edition

ISBN:9781305658004

Author:Ron Larson

Publisher:Ron Larson

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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	4,500
450	5,500
550	5,900
600	6,400
700	6,900
750	7,500

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 b0 (to 1 decimal). Do not round intermediate calculations.



Complete the estimated regression equation (to 1 decimal). Do not round intermediate calculations.

y= + x
b. What is the variable cost per unit produced (to 2 decimal)? Do not round intermediate calculations.
$

c. Compute the coefficient of determination (to 3 decimals). Do not round intermediate calculations. Note: report r^2 between 0 and 1 .


What percentage of the variation in total cost can be explained by the production volume (to 1 decimal)? Do not round intermediate calculations.
%

d. The company's production schedule shows 500 units must be produced next month. Predict the total cost for this operation (to the nearest whole number). Do not round intermediate calculations.

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