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 regressionequation 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 amanufacturing operation.Production Volume (units)Total Cost ($)400400045050005505400590060070064007000750a. Compute bị and bo (to 2 decimals if necessary).bịboComplete the estimated regression equation (to 2 decimals if necessary).хb. What is the variable cost per unit produced (to 1 decimal)?c. Compute the coefficient of determination (to 4 decimals). Note: report r between 0 and 1.=What percentage of the variation in total cost can be explained by the production volume (to 2 decimals)?d. The company's production schedule shows 500 units must be produced next month. What is the estimated total cost for this operation (to 2 decimals)?

a.Let X be the production volume and Y be the total costFrom the given data

Answered: An important application of regression…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

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HP-See What's Hot D D HP Games Web Slice Gallery bo Pokemon Best Wis... MINDTAP Q Search this course 8 X 15 Assignment 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 Σ 450 550 600 700 750 Compute bi and bo (to 1 decimal). Do not round intermediate calculations. b₁ Apple Yahoo! 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. Google Maps Total Cost ($) 4,300 5,300 5,700 6,200 6,700 7,300 Complete the estimated regression equation (to 1 decimal) Do not round…
An important application of regression analysis in accounting is in the estimation of cost. By collecting data on volume and cost and using the least squares method to develop an estimated regression equation relating volume and cost, an accountant can estimate the cost associated with a particular manufacturing volume. Consider the following sample of production volumes and total cost data for a manufacturing operation. Production Volume (units) Total Cost ($) 400 3,700 450 4,700 550 5,100 600 5,600 700 6,100 750 6,700 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. Compute bị and bo (to 1 decimal). Do not round intermediate calculations. b1 bo Complete the estimated regression equation (to 1 decimal). Do not round intermediate calculations. ŷ = + b. What is the variable cost per unit produced (to 2 decimal)? Do not round intermediate calculations. $ c.…
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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 (2018) Volume of Production (Units) Total Costs ($) Jan 500 6000 Feb 350 4000 Mar 450 5000 Apr 550 5400 May 600 5900 Jun 400 4000 Jul 400 4200 Aug 350 3900 Sept 400 4300 Oct 600 6000 Nov 700 6400 Dec 750 7000 1) Which of the following is NOT necessarily true about the interpretation of the value of b in the simple linear regression equation y = a + bx for this problem? 2) Which of the following statements are true about the dependent (or response) and independent (or predictor) variables for the simple linear model in…
An important application of regression analysis in accounting is in the estimation of cost. By collecting data on volume and cost and using the least squares method to develop an estimated regression equation relating volume and cost, an accountant can estimate the cost associated with a particular manufacturing volume. Consider the following sample of production volumes and total cost data for a manufacturing operation. Production Volume (units) Total Cost ($) 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
Urgent and important question 3rd
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 O and total cost data for a manufacturing operation. O Production Volume (units) Total Cost ($) 400 4100 450 4600 500 5600 600 6400 700 7400 750 8400 N The data on the production volume and total cost y for particular manufacturing operation were used to develop the estimated regression equation ŷ = -524.58+11.66z. a. The company's production schedule shows that 550 units must be produced next month. Predict the total cost for next month. ŷ* = (to 2 decimals) b. Develop a 98% prediction interval for the total cost for next month. X (to 2 decimals) 8 t-value (to 3 decimals) 8pred (to 2 decimals) Prediction Interval for…
An important application of regression analysis in accounting is in the estimation of cost. By collecting data on volume and cost and using the least squares method to develop an estimated regression equation relating volume and cost, an accountant can estimate the cost associated with a particular manufacturing volume. Consider the following sample of production volumes and total cost data for a manufacturing operation. Production Volume (units) Total Cost ($) 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)?
The value of a sports franchise is directly related to the amount of revenue that a franchise can generate. The following data represents the value in 2014 (in $millions) and the annual revenue (in $millions) for the 30 Major League Baseball franchises. Suppose you want to develop a simple linear regression model to predict franchise value based on annual revenue generated. Team Revenue Value Baltimore 245 1000 Boston 370 2100 Chicago White Sox 227 975 Cleveland 207 825 Detroit 254 1125 Houston 175 800 Kansas City 231 700 Los Angeles Angels 304 1300 Minnesota 223 895 New York Yankees 508 3200 Oakland 202 725 Seattle 250 1100 Tampa Bay 188 625 Texas 266 1220 Toronto 226 870 Arizona 211 840 Atlanta 267 1150 Chicago Cubs 302 1800 Cincinnati 227 885 Colorado…
An important application of regression analysis in accounting is in the estimation of cost. By collecting data on volume and cost and using the least squares method to develop an estimated regression equation relating volume and cost, an accountant can estimate the cost associated with a particular manufacturing volume. Consider the following sample of production volumes and total cost data for a manufacturing operation. Production Volume (units) Total Cost ($) 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…

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