An Important application of regresslon 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 regresslon 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. Total Cost ($) Production Volume (units) 400 4,100 450 5,100 550 5,400 600 6,000 700 6,500 750 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. (Round your numerical values to two decimal places.) (b) What is the variable cost (in dollars) per unit produced?

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How do I solve for the variable cost per unit produced?
An Important application of regresslon 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 regresslon
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.
Total Cost
($)
Production Volume
(units)
400
4,100
450
5,100
550
5,400
600
6,000
700
6,500
750
7,000
(a) Use these data to develop an estimated regression equation that could be used to predict the total cost for a given production volume. (Round your numerical values to two decimal places.)
(b) What is the variable cost (in dollars) per unit produced?
Transcribed Image Text:An Important application of regresslon analysis in accounting is in the estimation of cost. By collecting data on volume and cost and using the least squares method to develop an estimated regresslon equation relating volume and cost, an accountant can estimate the cost associated with a particular manufacturing volume. Consider the following sample of production volumes and total cost data for a manufacturing operation. Total Cost ($) Production Volume (units) 400 4,100 450 5,100 550 5,400 600 6,000 700 6,500 750 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. (Round your numerical values to two decimal places.) (b) What is the variable cost (in dollars) per unit produced?
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