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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 4000
450 5000
550 5400
600 5900
700 6400
750 7000
Compute b1 and b0 (to 2 decimals if necessary). b1 b0 Complete the estimated regression equation (to 2 decimals if necessary).

User MetaChrome
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1 Answer

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Answer:

Y = 7.60X + 1246.67

Explanation:

Given the data:

Production Volume (units) Total Cost ($)

400 4000

450 5000

550 5400

600 5900

700 6400

750 7000

Using technology, the linear regression calculator, the regression model obtained by fitting the data is :

Y = 7.60X + 1246.67 ; which is the model giving the relationship between Production volume, x and total cost, y.

Slope = 7.60

Intercept = 1246.67

User Phreeskier
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