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. A) Compute b1 and b0 (to 2 decimals if necessary). b1 = b0 = Complete the estimated regression equation (to 2 decimals if necessary). Ĺ· = _____ + _____x B) What is the variable cost per unit produced (to 1 decimal)? C) Compute the coefficient of determination (to 4 decimals). Note: report r^2 between 0 and 1. r^2 = What percentage of the variation in total cost can be explained by the production volume (to 2 decimals)? D) The company's production schedule shows 500 units must be produced next month. What is the estimated total cost for this operation (to 2 decimals)? $______
Added by Javier C.
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6. This means that for each additional unit of production volume, the total cost increases by 17.6 units. You have also calculated the variable cost per unit produced as 7.6. This is the cost associated with producing one additional unit, once fixed costs have Show more…
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An important application of regression analysis in accounting is in the estimation of cost. By collecting data on volume and cost and using the least squares method to develop an estimated regression equation relating volume and cost, an accountant can estimate the cost associated with a particular manufacturing volume. Consider the following sample of production volumes and total cost data for a manufacturing operation. Production Volume (units) Total Cost ($) 400 4,000 450 4,900 550 5,500 600 5,800 700 6,300 750 6,900 (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.) Ĺ· = (b) What is the variable cost (in dollars) per unit produced? $ (c) Compute the coefficient of determination. (Round your answer to three decimal places.) What percentage of the variation in total cost can be explained by production volume? (Round your answer to one decimal place.) % (d) The company's production schedule shows 650 units must be produced next month. Predict the total cost (in dollars) for this operation. (Round your answer to the nearest cent.) $
David N.
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)? $
Madhur L.
Refer to exercise $21,$ where data on the production volume $x$ and total cost $y$ for a particu- lar manufacturing operation were used to develop the estimated regression equation $\hat{y}=$ $1246.67+7.6 x .$ $$ \begin{array}{l}{\text { a. The company's production schedule shows that } 500 \text { units must be produced next }} \\ {\text { month. What is the point estimate of the mean total cost for next month? }} \\ {\text { b. Develop a } 99 \% \text { prediction interval for the total cost for next month. }}\end{array} $$ $$ \begin{array}{l}{\text { c. If an accounting cost report at the end of next month shows that the actual production }} \\ {\text { cost during the month was } \$ 6000, \text { should managers be concerned about incurring such }} \\ {\text { a high total cost for the month? Discuss. }}\end{array} $$
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