Cost Estimation

Question 1

Scattergraphs

Answer 1

Graphs that plot costs against activity levels

Question 2

What is a common rule of thumb for determining then umber of observations in statistical cost estimation

Answer 2

Use three years of monthly data if the physical processes have not changed significantly within that time

Question 3

Slop of the line

Answer 3

Variable costs per unit

Question 4

Intercept with the vertical axis

Answer 4

estimate of the fixed costs

Question 5

high-low cost

Answer 5

method to estimate costs based on two cost observations, usually at the highest and lowest activity levels

Question 6

In H-L Cost estimation, calculate variable cost per unit

Answer 6

Variable cost per unit = (cost at highest activity level-cost at lowest activity level)/(highest activity level-Lowest Activity level)

Question 7

In H-L Cost estimation, calculate Fixed cost

Answer 7

Fixed cost = Total cost at highest [or lowest] activity level - (Variable cost X Highest [or lowest] activity level)

Question 8

Regression

Answer 8

Statistical procedure to determine the relation between variables. Generates a line that best fits a set of data points. Because the regression procedure uses all the data points, the resulting estimates have a broader base than those based on a few select points (like the h-l method).
Also allows for more than one predictor (x variable).
Regression programs accept any data for Y and X terms so the accountant must be careful that data entered has a logical relation so it doesn’t result in misleading estimates.

Question 9

Independent variable

Answer 9

predictor, x terms

Question 10

Dependent variable

Answer 10

y term, Left-hand side

Question 11

Correlation Coefficients

Answer 11

R, measures the linear relation between two or more variables, such as cost and some measure of activity.
Measures the proximity of the data points to the regression line.

The closer R is to 1.0, the closer the data points are to the regression line.
Conversely, the closer R is to zero, the poorer the fit of the regression line.

Question 12

Coefficient of determination

Answer 12

R^2, Square of the correlation coefficient, interpreted as the proportion of the variation in the dependent variable explained by the independent variables.

If R squared is .828, it can be said that 82.8% of the changes in dependent costs can be explained by changes in the independent variable.

Question 13

Ordinary least squares regression OLS

Answer 13

Regression line is computed so that the sum of the squares of the vertical distances from each point to the line is minimized. Organizations often exclude data for periods of unusual occurrences like strikes, extreme weather, and shutdowns.

Question 14

t-statistic

Answer 14

t= b / SE

t is the value of the estimated coefficient, b, divided by its standard error.
Generally, a t-statistic greater than 2 is considered significant.

To construct a 95 percent confidence interval around b, we add or subtract to b the appropriate t-value for the 95% confidence interval times the standard error of b in

b +- t x (SE of b)

Question 15

adjusted R-squared

Answer 15

correlation coefficient squared and adjusted for the number of independent variables used to make the estimate.
Adjusted R squared value is a better measure of the association between X and Y than the unadjusted R squared when more than one X predictor is used.

Question 16

Common problems with regression estimates

Answer 16

1. Attempting to fit a linear equation to nonlinear data
2. Failing to exclude outliers
3. Including predictors with apparent, but spurious, relations to the dependent variable.
4. using data that do not fit the assumptions of regression analysis.

Question 17

Effect of nonlinear relations on regression analysis

Answer 17

Likely to occur when the firm is operating near its capacity limits. Close to maximum capacity, costs increase more rapidly than activity because of overtime premiums paid to employees, increased maintenance, and repair costs for equipment…
To overcome, define a relevant range of activity (for example from 25-75 percent)

Question 18

Effect of Outliers (example) in regression analysis

Answer 18

A single year’s worth of supplies was purchased and expensed entirely (but not used) within a single month or a large adjustment was made for under accruing payroll taxes. The accounting records are clearly abnormal with respect to the activity measure.

To overcome, use a scattergraph first and remove the highly unusual observations before running the regression.

Question 19

Effect of spurious relations in regression analysis

Answer 19

Accountants must think through the relationships and not just let excel find the relationships among many variables. This can lead to misleading results.

Question 20

Two assumptions of Regression analysis

Answer 20

The process for which costs are being estimated remains constant over time AND

The errors in estimating the costs are independent of the cost drivers.

Question 21

learning Phenomenon

Answer 21

Systematic relationship between the amount of experience in performing a task and the time required to perform it. The variable costs tend to decrease per unit as the volume of activity increases.

Example: 80% learning curve–The time to produce the 4th unit is 80% of the second. The time to produce the 10th unit is 80% of the 5th unit.

Question 22

Cost estimation assumption methods

Answer 22

Cost behavior depends on just one cost driver (multiple regression is an exception)

Cost behavior patterns are linear within the relevant range.

Question 23

Account analysis

Answer 23

Cost estimation method that calls for a review of each account making up the total cost being analyzed.

Uses the experience and judgment of managers and accountants who are familiar with company operations and the way costs react to changes in activity levels. Relies on personal judgment. Includes the realities of downtime, missed work, machine repair, and the other factors that often cause engineering estimates to be less than realistic.