Sampling

Question 1

Attribute Sampling

Answer 1

Testing for presence/absence of an “attribute”

- useful for tests of control procedures

Question 2

Variable Sampling

Answer 2

Estimating a value +/- some range. Useful for substantive testing

Question 3

Sampling Risk

Answer 3

Risk of wrong conclusion because the sample is not representative of population (by chance)

Question 4

Non-Sample Risk

Answer 4

Risk of wrong conclusion by incorrectly applying sampling procedures (human error)

Question 5

Risk of not auditing enough

Answer 5

Beta risk, or risk of being wrong

Question 6

ARACR

From Attribute Sampling

Answer 6

Acceptable Risk of assessing CR too low.

• Attribute sampling concluding, through performing test of controls, that controls are functioning , when they are not.
• Consequence: CR too low —> not enough substantive testing because DR is too high

Question 7

ARAIA

From Variable Sampling

Answer 7

Acceptable Risk of incorrect acceptance = accepting (failing to reject) the account as being fairly stated when it is not.
- Consequence: unmodified opinion when FS is actually materially misstated.

Question 8

Tolerable Exception Rate (TER)

Answer 8

For Attribute Sampling
Acceptable error % where you can say the control is functioning. Amount of deviation you can accept and say control is good.

Question 9

Tolerable Misstatement

Answer 9

For Variable Sampling (Substantive Testing)

- account materiality in substantive testing.

Question 10

Expected Population Exception Rate (EPER)

Answer 10

Attribute Sampling - Estimated from prior experience

Question 11

Anticipated Misstatement (AM)

Answer 11

Variable Sampling - Expected amount of error based on prior experience

Question 12

CUER

Answer 12

Attribute Sampling - Computed upper exception rate -is the worst possible population error rate implied by these sample results.
- Compared to TER

Question 13

Types of Variable Sampling

Answer 13

• Monetary Unit Sampling, AKA PPS

- Mean per Unit

Question 14

Monetary Unit Sampling or PPS

Answer 14

• is an attribute sampling method applied to a variable sampling application
• Use when expect few errors
• requires no knowledge of distributional properties
• $ is sample unit

Question 15

Mean per Unit (MPU) Sampling

Answer 15

estimate a balance +/- some range

• uses sample values to estimate population total values
• Relies on normal distribution theory

Question 16

PPS sample size formula

Answer 16

N = BV x RF/ TM - (AM x EF)
*RF & EF are explosion factors determined by beta (ARIA) risk
RF = reliability factor
EF = expansion factor

Question 17

Difference Estimation

Answer 17

same as MPU, but measure the amount of error in each sample item instead of the item’s value.
- use if you expect a lot of errors

Question 18

Ratio Estimation

Answer 18

Same as difference estimation, but measure the % error in each same item rather than the $ error. Use if you expect errors the errors have a predicable relationship to the amount of the item.

Question 19

If fraud or gross error is suspected in the population, the auditor would most likely use

Answer 19

Discovery sampling

Question 20

Projected Error in PPS

Answer 20

BV-Audit = Known Error
Known Error/ Book Value = % Error
% Error x $Sample Interval = $ projected error