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 ($) January 2018 February 2018 500 6,000 350 4,000 March 2018 450 5,000 April 2018 May 2018 550 5,400 600 5,900 June 2018 400 4,000 July 2018 August 2018 September 2018 400 4,200 350 3,900 400 4,300 October 2018 600 6,000 November 2018 700 6,400 December 2018 750 7,000
An important application of regression analysis is in the estimation of cost. By collecting data on volume and cost and using the least squares method to develop an estimated regression equation relating volume and cost, one can estimate the cost associated with a particular manufacturing volume. Consider the following sample of monthly production volumes and total costs data for a manufacturing operation for the year 2018. Month Production Volume (units) Total Costs ($) January 2018 February 2018 500 6,000 350 4,000 March 2018 450 5,000 April 2018 May 2018 550 5,400 600 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
Linear Algebra: A Modern Introduction
4th Edition
ISBN:9781285463247
Author:David Poole
Publisher:David Poole
Chapter7: Distance And Approximation
Section7.3: Least Squares Approximation
Problem 31EQ
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