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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) Compute by and bo (to 1 decimal). b₁ bo 400 450 550 600 700 750 a. Use these data to develop an estimated regression equation that could be used to predict the total cost for a given production volume. Do not round intermediate calculations. Complete the estimated regression equation (to 1 decimal). Do not round intermediate calculations. ŷ = + Total Cost ($) 4,000 5,000 5,400 5,900 6,400 7,000 b. What is the variable cost per unit produced (to 2 decimal)? Do not round intermediate calculations $ c. Compute the coefficient of determination (to 3 decimals). Do not round intermediate calculations. Note: report 2 between 0 and 1. p² = What percentage of the variation in total cost can be explained by the production volume (to 1 decimal)? Do not round intermediate calculations % d. The company's production schedule shows 500 units must be produced next month. Predict the total cost for this operation (to the nearest whole number). Do not round intermediate calculations $

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) Compute by and bo (to 1 decimal). b₁ bo 400 450 550 600 700 750 a. Use these data to develop an estimated regression equation that could be used to predict the total cost for a given production volume. Do not round intermediate calculations. Complete the estimated regression equation (to 1 decimal). Do not round intermediate calculations. ŷ = + Total Cost ($) 4,000 5,000 5,400 5,900 6,400 7,000 b. What is the variable cost per unit produced (to 2 decimal)? Do not round intermediate calculations $ c. Compute the coefficient of determination (to 3 decimals). Do not round intermediate calculations. Note: report 2 between 0 and 1. p² = What percentage of the variation in total cost can be explained by the production volume (to 1 decimal)? Do not round intermediate calculations % d. The company's production schedule shows 500 units must be produced next month. Predict the total cost for this operation (to the nearest whole number). Do not round intermediate calculations $

Elementary Linear Algebra (MindTap Course List)
Elementary Linear Algebra (MindTap Course List)
8th Edition
ISBN:9781305658004
Author:Ron Larson
Publisher:Ron Larson
Chapter2: Matrices
Section2.CR: Review Exercises
Problem 90CR
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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) 400 450 550 Compute bi and bo (to 1 decimal). b₁ bo 600 700 750 a. Use these data to develop an estimated regression equation that could be used to predict the total cost for a given production volume. Do not round intermediate calculations. Complete the estimated regression equation (to 1 decimal). Do not round intermediate calculations ŷ = + I Total Cost ($) 4,000 5,000 5,400 5,900 6,400 7,000 b. What is the variable cost per unit produced (to 2 decimal)? Do not round intermediate calculations $ c. Compute the coefficient of determination (to 3 decimals). Do not round intermediate calculations. Note: report ² between 0 and 1. p² = What percentage of the variation in total cost can be explained by the production volume (to 1 decimal)? Do not round intermediate calculations % d. The company's production schedule shows 500 units must be produced next month. Predict the total cost for this operation (to the nearest whole number). Do not round intermediate calculations $
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 (units) 400 450 550 Compute bi and bo (to 1 decimal). b₁ bo 600 700 750 a. Use these data to develop an estimated regression equation that could be used to predict the total cost for a given production volume. Do not round intermediate calculations. Complete the estimated regression equation (to 1 decimal). Do not round intermediate calculations ŷ = + I Total Cost ($) 4,000 5,000 5,400 5,900 6,400 7,000 b. What is the variable cost per unit produced (to 2 decimal)? Do not round intermediate calculations $ c. Compute the coefficient of determination (to 3 decimals). Do not round intermediate calculations. Note: report ² between 0 and 1. p² = What percentage of the variation in total cost can be explained by the production volume (to 1 decimal)? Do not round intermediate calculations % d. The company's production schedule shows 500 units must be produced next month. Predict the total cost for this operation (to the nearest whole number). Do not round intermediate calculations $
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