12. DETAILS ASWSBE14 14.E.021. MY NOTES ASK YOUR TEACHER PRACTICE ANOTHER 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 Total Cost (units) (S) 400 4,100 450 5,000 550 5,500 600 5,900 700 6,500 750 7,000 (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.) (b) What is the variable cost (in dollars) per unit produced?

12. DETAILS ASWSBE14 14.E.021. MY NOTES ASK YOUR TEACHER PRACTICE ANOTHER 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 Total Cost (units) (S) 400 4,100 450 5,000 550 5,500 600 5,900 700 6,500 750 7,000 (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.) (b) What is the variable cost (in dollars) per unit produced?

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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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 ($) 400 3,800 450 4,800 550 5,200 600 5,700 700 6,200 750 6,800 a. Compute b1 and bo (to 1 decimal). b1 bo Complete the estimated regression equation (to 1 decimal). + b. What is the variable cost per unit produced (to 1 decimal)? c. Compute the coefficient of determination (to 3 decimals). Note: report r between 0 and 1. What percentage of the variation in total cost can be explained by the production volume (to 1 decimal)? d. The company's production schedule shows 500 units must be produced next month. What is the estimated total…
Report the equation of the regression line and interpret it in the context of the problem
You may need to use the appropriate appendix table or technology to answer this question. The below data on the production volume x and total cost y (in dollars) for a particular manufacturing operation were used to develop the estimated regression equation ŷ = 1,401.33 + 7.36x. Production Volume Total Cost (units) ($) 400 4,000 450 5,100 550 5,400 600 6,000 700 6,300 750 7,000 (a) The company's production schedule shows that 500 units must be produced next month. What is the point estimate of the total cost (in dollars) for next month? (Round your answer to the nearest cent.) $ (b) Develop a 99% prediction interval for the total cost (in dollars) for next month. (Round your answers to the nearest cent.) to $ (c) If an accounting cost report at the end of next month shows that the actual production cost during the month was $6,500, should managers be concerned about incurring such a high total cost for the month? Discuss. Since $6,500 is ---Select---v the prediction interval, managers…
An important application of regression analysis in accounting is in the estimation of cost. By collecting data on volume and cost and using the least squares method to develop an estimated regression equation relating volume and cost, an accountant can estimate the cost associated with a particular manufacturing volume. Consider the following sample of production volumes and total cost data for a manufacturing operation. Production Volume (units) Total Cost ($) 400 4,300 450 5,300 550 5,700 600 6,200 700 6,700 750 7,300 Compute b1 and b0 (to 1 decimal). Complete the estimated regression equation (to 1 decimal) y^ = ____ + ____x What is the variable cost per unit produced (to 1 decimal)?
An important application of regression analysis 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, one can estimate the cost associated with a particular manufacturing volume. Consider the following sample of monthly production volumes and total costs data for a manufacturing operation for the year 2018. Month Production Volume (units) Total Costs ($) January 2018 February 2018 500 6,000 350 4,000 March 2018 450 5,000 April 2018 550 5,400 May 2018 600 5,900 June 2018 400 4,000 July 2018 August 2018 September 2018 400 4,200 350 3,900 400 4,300 October 2018 600 6,000 November 2018 700 6,400 December 2018 750 7,000 Which of the following is NOT necessarily true about the interpretation of the value of b in the simple linear regression equation y = a + bx for this problem? * I. The monthly total costs will increase by $7.6437 for every one-unit increase in the…
An important application of regression analysis in accounting is in the estimation of cost. By collecting data on volume and cost and using the least squares method to develop an estimated regression equation relating volume and cost, an accountant can estimate the cost associated with a particular manufacturing volume. Consider the following sample of production volumes and total cost data for a manufacturing operation. Production Volume (units) Total Cost ($) 400 4,700 450 5,700 550 6,100 600 6,600 700 7,100 750 7,700 A) Compute b1 and b0 (to 1 decimal)b1 b0 Complete the estimated regression equation (to 1 decimal). = + x B) What is the variable cost per unit produced (to 1 decimal)?$ C) 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)? % D) The company's production schedule shows 500 units must be produced next…
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. Total Cost ($) 3900 4700 5300 5700 6400 7100 The data on the production volume and total cost y for particular manufacturing operation were used to develop the estimated regression equation =-490.00 + 10.60x, a. The company's production schedule shows that 450 units must be produced next month. Predict the total cost for next month. ŷ* = * (to 2 decimals) b. Develop a 99% prediction interval for the total cost for next month. (to 2 decimals) 8 t- value decimals) (to 3 * (to 2 Spred decimals) Prediction Interval for an individual Value next month Ⓡ Production Volume…