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 Total Cost(Units) ($)400 4,000450 5,000550 5,400600 5,900700 6,400750 7,000Use the data to develop an estimated regression equation that could be used to predict the total cost for a given production volume.what is the variable cost per unit produced?

Respuesta :

Answer:

a. y = 1246.667 + 7.6x

b $7.6 per unit

Explanation:

a..

Given

n = 6.

Solving the regression equation using

y = a + bx

See attachment for solution

a = 1246.667

b = 7.3

So, y = 1246.667 + 7.3x

b.

The Variable cost per unit is given by the slope of the regression equation i.e. the coefficient of x

Which is 7.6

Ver imagen MrRoyal
Ver imagen MrRoyal

Answer:

Regression equation: Y = 1,246.67 + 7.6X

Variable cost per unit = $7.6

Explanation:

The regression equation will be in the form [tex]Y = a + bX[/tex]

Where Y = total cost,

X = production volume,

a = constant, i.e. total cost when production volume = 0,

b = variable cost.

"b" and "a" can be computed as follows:

[tex]b = \frac{NEXY - EXEY}{NEX^{2} - (EX)^{2} }[/tex] (letter "E" was used in the place of summation)

[tex]a = \frac{EY - bEX}{N}[/tex]

The computation of the variables in the above equation are done in the file attached.

thus [tex]b = \frac{(6*20,090,000) - (3,450*33,700)}{(6*2,077,500) - (3,450)^{2} }[/tex]

= [tex]\frac{120,540,000 - 116,265,000}{12,465,000 - 11,902,500}\\[/tex]

= 7.6

and

[tex]a = \frac{33,700-(7.6*3,450)}{6}[/tex]

= 1,246.67.

Therefore, the regression equation is Y = 1,246.67 + 7.6X.

Variable cost per unit produced is "b" = $7.6.