A10 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 todevelop an estimated regression equation relating volume and cost, an accountant can estimate the cost associated with a particular manufacturing volume. Considerthe following sample of production volumes and total cost data for a manufacturing operation.Production Volume Total Cost(units)($)4004505506007007504,1005,0005,3005,9006,3006,900(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 numericalvalues to two decimal places.)(b) What is the variable cost (in dollars) per unit produced?7.6X(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 tothe nearest cent.)

Production Volume (Units)Total Cost ($)400410045050005505300600590070063007506900

Answered: An important application of regression…

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter13: Regression And Forecasting Models

Section13.4: Multiple Regression Models

Problem 17P: The owner of a restaurant in Bloomington, Indiana, has recorded sales data for the past 19 years. He...

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1. Problem: If a car driven 50,000 miles, how much would be the maintenance cost? 2. Use Linear Regression equation to find the maintenance cost. Show step by step calculations. 3. Also, calculate r^2 for the above model. Show step by step calculations.
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Problem 3 Picante Corporation expects demand for mp3 players that they produce to increase. Demand for their mp3 players for last year was as follows: MONTH JANUARY FEBRUARY MARCH APRIL 2,150 2,000 2,200 AUGUST SEPTEMBER OCTOBER 2,450 2,700 2,850 DEMAND 2,100 MONTH JULY DEMAND 2,650 MAY JUNE 2,500 2,350 NOVEMBER DECEMBER 3,150 3,000 a. Using least squares regression analysis, what would you estimate demand to be for each month next year? b. To be reasonably confident of meeting demand, Picante Corporation decides to use three standard errors of estimate for safety. How many additional units should be held to meet this level of confidence?

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