Question

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 4,000 450 5,000 550 5,400 600 5,900 700 6,400 750 7,000 a. Compute b1 and bo (to 1 decimal).(need help) 7.6 +1346.7 Complete the estimated regression equation (to 1 decimal). 1346.7 (need help) 7.6 b. What is the variable cost per unit produced (to 1 decimal)? 7.6 c. Compute the coefficient of determination (to 3 decimals). Note: report between and r2= . 0.959 What percentage of the variation in total cost can be explained by the production volume (to 1 decimal)? 95.9 d. The company's production schedule shows units must be produced next month. What is the estimated total cost for this operation (to the nearest whole number)? 5146.7 (need help)

Answer #1

Volume (X) | Cost (Y) | X * Y | X2 | Y2 | |

400 | 4000 | 1600000 | 160000 | 16000000 | |

450 | 5000 | 2250000 | 202500 | 25000000 | |

550 | 5400 | 2970000 | 302500 | 29160000 | |

600 | 5900 | 3540000 | 360000 | 34810000 | |

700 | 6400 | 4480000 | 490000 | 40960000 | |

750 | 7000 | 5250000 | 562500 | 49000000 | |

Total | 3450 | 33700 | 20090000 | 2077500 | 1.95E+08 |

b1 = 7.6

b0 =( Σ Y - ( b * Σ X) ) / n

b0 =( 33700 - ( 7.6 * 3450 ) ) / 6

b0 = 1246.667

Equation of regression line becomes Ŷ = 1246.6667 +
7.6X

The variable cost per unit produced is $7.6

r = 0.979

Coefficient of Determination

R2 = r2 = 0.959

Explained variation = 0.959* 100 = 95.9%

When X = 5146.7

Ŷ = 1246.667 + 7.6 X

Ŷ = 1246.667 + ( 7.6 * 5146.7 )

Ŷ = 40361.59

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
4,000
450
5,000
550
5,400
600
5,900
700
6,400...

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
4,000
450
5,000
550
5,400
600
5,900
700
6,400...

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
4,500
450
5,500
550
5,900
600
6,400
700
6,900...

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
4,500
450
5,500
550
5,900
600
6,400
700
6,900...

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
4,400
450
5,400
550
5,800
600
6,300
700
6,800...

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...

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.
In the Microsoft Excel Online file below you will find a sample
of production volumes and total cost data for a manufacturing
operation. Conduct a regression analysis to explore the
relationship...

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
4000
450
5000
550
5400
600
5900
700
6400...

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
4,100
450
5,100
550
5,300
600
5,800
700
6,300...

An important application of regression analysis is the
estimation of cost, particularly the effect of production volume on
total cost. The following data come from a company which has kept
track of production volume and total cost at several different
levels of production.
Production volume (units)
Total cost ($)
400
4000
450
5000
550
5400
600
5900
700
6400
750
7000
Use these data to estimate a regression designed to capture the
effect of production volume on the total cost....

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