Cost Estimation Flashcards

1
Q

What are 2 methods for splitting mixed costs into variable & fixed components?

A

High-low method

Least squares regression method/linear regression

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2
Q

What is a COST DRIVER?

A

An activity that is identified for each cost

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3
Q

What does measuring costs mean?

A

To measure how a cost change in response to a change in activity

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4
Q

How do you choose a cost driver?

A

Choose the one that causes the costs to be incurred.

If a change in the cost driver would cause the cost to change.

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5
Q

What does plausibility of the cost driver mean?

A

That the cost would be significantly affected by changes in the activity

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6
Q

Can costs be driven by only one cost driver?

A

No, it can be driven by more than one

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7
Q

What is a SCATTER graph?

A

A GRAPHICAL method of cost estimation that plots various observations of costs against the activity level

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8
Q

How is the scatter graph’s line drawn?

A

According to your own visual judgement

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9
Q

What indicates the fixed cost portion on the scatter graph?

A

The intercept (on the assumption that it falls within the relevant range)

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10
Q

Is the scatter graph accurate?

A

No, it is not very accurate

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11
Q

What is the HIGH-LOW method?

A

A MATHEMATICAL approach to split a mixed cost into its variable and fixed components

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12
Q

What is the equation for a linear relationship for the high-low method?

A

The regression equation: y = mx + c

y: total (aggregate cost)
m: gradient or slope of the line (variable cost per unit of the cost driver)
x: cost driver level
c: where the line intercepts the y-axis (fixed cost)

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13
Q

In the regression equation, what is the dependent and independent variable?

A
y = the dependent variable (y is DEPENDENT on x)
x = the independent variable
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14
Q

What is the flaws of the high-low method?

A
  1. Only 2 points are selected (no coverage of population)

2. These points are extremes and may not be representative of the population (or lie outside the relevant range)

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15
Q

What is the LEAST SQUARES REGRESSION method?

A

A STATISTICAL approach to establishing the equation of the line that best fits all of the data points provided

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16
Q

What is a best fit line?

A

A line that reduces the sum of the squares of the regression errors.

17
Q

What is a regression error?

A

The distance between the line and the point/observation (all points not on the line)

18
Q

What approach is the most accurate?

A

The least squares regression, but it is also the most tedious