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. Compute  and  (to 1 decimal).     Complete the estimated regression equation (to 1 decimal).

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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. Compute  and  (to 1 decimal).
 
 

Complete the estimated regression equation (to 1 decimal).
    

b. What is the variable cost per unit produced (to 1 decimal)?


c. Compute the coefficient of determination (to 3 decimals). Note: report  between  and .
 

What percentage of the variation in total cost can be explained by the production volume (to 1 decimal)?
 

d. The company's production schedule shows  units must be produced next month. What is the estimated total cost for this operation (to the nearest whole number)?
 

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