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 Total Cost (units) ($) 400 3,900 450 5,100 550 5,300 600 5,800 700 6,300 750 7,000 (a) Use these data to develop an estimated regression equation that could be used to predict the total cost for a given production volume. (Round your numerical values to two decimal places.) -1243.67 +7.52x
An important application of regression analysis in accounting is in the estimation of cost. By collecting data on volume and cost and using the least squares method to develop an estimated regression equation relating volume and cost, an accountant can estimate the cost associated with a particular manufacturing volume. Consider the following sample of production volumes and total cost data for a manufacturing operation. Production Volume Total Cost (units) ($) 400 3,900 450 5,100 550 5,300 600 5,800 700 6,300 750 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.) -1243.67 +7.52x
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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 Total Cost
(units)
($)
400
3,900
450
5,100
550
5,300
600
5,800
700
6,300
750
7,000
(a) Use these data to develop an estimated regression equation that could be used to predict the total cost for a given production volume. (Round your
numerical values to two decimal places.)
-1243.67 +7.52x](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F7a1c1730-4c92-4161-b3da-24feb6553e9f%2F600cc66c-64b1-4009-a93d-0aafe23fefff%2F6cpuu33_processed.png&w=3840&q=75)
Transcribed Image Text:An important application of regression analysis in accounting is in the estimation of cost. By collecting data on volume and cost and using the least squares
method to develop an estimated regression equation relating volume and cost, an accountant can estimate the cost associated with a particular
manufacturing volume. Consider the following sample of production volumes and total cost data for a manufacturing operation.
Production Volume Total Cost
(units)
($)
400
3,900
450
5,100
550
5,300
600
5,800
700
6,300
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.)
-1243.67 +7.52x
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