5-18 high-low - II Problem 5-19 (Appendix 5A) Least-Squares...

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II Problem 5-19 (Appendix 5A) Least-Squares Regression Method [LO5] Sebolt Wire Company heats copper ingots to very high temperatures by placing the ingots in a large heat coil. The heated ingots are then run through a shaping machine that shapes the soft ingot into wire. Due to the long heat-up time, the coil is never turned off. When an ingot is placed in the coil, the temperature is raised to an even higher level, and then the coil is allowed to drop to the "waiting" temperature between ingots. Management needs to know the variable cost of power involved in heating an ingot and the fixed cost of power during "waiting" periods. The following data on ingots processed and power costs are available Month Ingots Power Cost January 110 $ 5,500 February 90 $ 4,500 March 80 $ 4,400 April 100 $ 5,000 May 130 $ 6,000 June 120 $ 5,600 July 70 $ 4,000 August 60 $ 3,200 September 50 $ 3,400 October 40 $ 2,400 Requirement 1: Using the least-squares regression method, estimate a cost formula for power cost, where "X" represents number of ingots processed. (Round the variable cost to the nearest cent and the fixed cost to the nearest dollar Y = $ ____ 1,185 ________ + $ _____ 37.82 _____ X Solution:- 1. The least squares regression method: Number of Ingots (X) Power Cost (Y) 110 $5,500 90 $4,500 80 $4,400 100 $5,000 130 $6,000
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120 $5,600 70 $4,000 60 $3,200 50 $3,400 40 $2,400 A spreadsheet application such as Excel or a statistical software package can be used to compute the slope and intercept of the least-squares regression line for the above data. The results are: Intercept (fixed cost). .................................... $1,185
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5-18 high-low - II Problem 5-19 (Appendix 5A) Least-Squares...

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