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.

1. Compute b₁ and b₀ (to 1 decimal).
   b₁
   b₀
   
   Complete the estimated regression equation (to 1 decimal).
   =  +  x
   
2. What is the variable cost per unit produced (to 1 decimal)?
   $
   
3. Compute the coefficient of determination (to 3 decimals). Note: report r² between 0 and 1.
   r² =
   
   What percentage of the variation in total cost can be explained by the production volume (to 1 decimal)?
   %
   
4. The company's production schedule shows 500 units must be produced next month. What is the estimated total cost for this operation (to the nearest whole number)?
   $

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 4,900 450 5,900 550 6,300 600 6,800 700 7,300 750 7,900

Compute b1 and b0 (to 1 decimal).

b1 b0 Complete the estimated regression equation (to 1 decimal).y= + x

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

Compute the coefficient of determination (to 3 decimals).

Note: report r2 between 0 and 1. r2 =

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

The company's production schedule shows 500 units must be produced next month.

What is the estimated total cost for this operation (to the nearest whole number)? $

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 4,900

450 5,900

550 6,300

600 6,800

700 7,300

750 7,900

Compute b1 and b0 (to 1 decimal). b1 b0 Complete the estimated regression equation (to 1 decimal). ŷ = + x

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

Compute the coefficient of determination (to 3 decimals). Note: report r2 between 0 and 1. r2 =

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

The company's production schedule shows 500 units must be produced next month.

What is the estimated total cost for this operation (to the nearest whole number)? $

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.

400 $4300

450 $5300

550 $5700

600 $6200

700 $6700

750 $7300

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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.

1. Compute b₁ and b₀ (to 1 decimal).
   b₁
   b₀
   
   Complete the estimated regression equation (to 1 decimal).
   = + x
   
2. What is the variable cost per unit produced (to 1 decimal)?
   $
   
3. Compute the coefficient of determination (to 3 decimals). Note: report r² between 0 and 1.
   r² =
   
   What percentage of the variation in total cost can be explained by the production volume (to 1 decimal)?
   %
   
4. The company's production schedule shows 500 units must be produced next month. What is the estimated total cost for this operation (to the nearest whole number)?
   $

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 4,700 450 5,700 550 6,100 600 6,600 700 7,100 750 7,700 Compute b1 and b0 (to 1 decimal). b1 b0 Complete the estimated regression equation (to 1 decimal). = + x What is the variable cost per unit produced (to 1 decimal)? $ Compute the coefficient of determination (to 3 decimals). Note: report r2 between 0 and 1. r2 = What percentage of the variation in total cost can be explained by the production volume (to 1 decimal)? % The company's production schedule shows 500 units must be produced next month. What is the estimated total cost for this operation (to the nearest whole number)? $

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.