Aud 6 Audit Sampling

Front 1

Statistical Sampling

Back 1

o Based on formulas
o Helps find an appropriate audit sample
o Helps evaluate evidence obtained
o Helps evaluate results and quantify Sampling
Risk

Front 2

Non-Statistical Sampling

Back 2

o Based on a human decision
o Equally acceptable as Statistical Sampling

Front 3

Substantive Tests

Back 3

o Variables Sampling
o Probability Proportionate to Size Sampling

Front 4

Control Tests

Back 4

o Attribute Sampling

Front 5

Risk of assessing Control Risk too high

Back 5

o A risk of Control Testing
o Auditor works to make Control Risk lower
 More substantive tests
o Sample overstates Control Risk
o Leads to an under-reliance on internal control,
over-testing, and overall audit inefficiency
 Audit ends up being effective (correct
result), but you do more work

Front 6

Risk of assessing Control Risk too low

Back 6

o A risk of Control Testing
o Complement to Confidence Level
o Inverse relationship to Sample Size
 Higher accepted risk of assessing Control
Risk too low = Smaller Sample
 Lower accepted risk of assessing Control
Risk too low = Larger Sample
o Auditor concludes controls are operating
effectively based on the sample
o Leads to higher Detection Risk
 Fewer Substantive Tests
o Sample understates Control Risk
o This error leads to over-reliance on internal
control, under testing, and overall audit
ineffectiveness
o Does NOT necessarily mean that the F/S are
materially misstated – it does mean that if
there is one, you are less likely to find it

Front 7

Incorrect Acceptance

Back 7

o A risk of Substantive Testing
o Auditor accepts a balance as fairly stated, when
in fact it is not fairly stated
 Hurts audit effectiveness
 Wrong conclusion reached
 Efficient, but not effective

Front 8

Incorrect Rejection

Back 8

o A risk of Substantive Testing
o Auditor rejects balance as fairly stated when in
fact it is fairly stated
 Hurts audit efficiency
 Wrong recommendations given
 Effective, but not efficient

Front 9

Classic Variables Sampling

Back 9

 Testing for a dollar amount
 Value in sample gives information about value in
entire population
 Mean Per Unit
o Sample Average x Number in Population
 Stratification
o Decreases effect of variance in population and
reduces sample size

Front 10

Probability Proportionate to Size (PPS)

Back 10

 A form of Variable Sampling
 Does NOT use Standard Deviation
 Auditor focuses on a dollar amount
 Larger or more valuable items get picked more often
as part of the sample
 Projected Misstatement
o Misstatement found in sample – have to project
it to remainder of population

Front 11

Formula for Audit Sampling

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 SER + ASR < TER

Sample Error Rate (SER)
Allowance for Sampling Risk (ASR)
Tolerable Error Rate (TER)

Front 12

Example of Sample Error Rate (SAR)

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o 5 out of 100 invoices were not approved
correctly
o Sample Error Rate = 5%

Front 13

Allowance for Sampling Risk (ASR)

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o The amount that you add to the SER to get
some cushion for your sample
o As high as you think the population error rate
could go based on experience
o ASR is set at 2%, based on judgment
o Population error rate could reach 7% (5+2)

Front 14

Tolerable Error Rate (TER)

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o The amount of error rate that you can accept
o If population error rate is less than TER
 Accept the Control as effective
o If population error rate is more than TER
 Do more testing to get SER lower or
 Conclude control isn’t effective
 Do more substantive testing

Front 15

Basic Steps in statistical plan (Testing Controls)

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1. Determine objectives of plan
2. Define population
3. Determine acceptable levels of sampling risk
4. Define deviation conditions or materiality level
5. Calculate the sample size
6. Select sampling approach
7. Take sample
8. Evaluate sample
9. Document sampling procedures

Front 16

Systematic Sampling

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 Every certain # of a population is selected
 Population needs to be randomly ordered
 Primary advantage

Front 17

Sequential Sampling

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 Also called “Stop or Go” Sampling
 Each audit step determines the next step

Front 18

Discovery Sampling

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 Audit is testing an area that is so crucial, then zero
population errors can be tolerated
o Any phony employees on payroll?

Front 19

Block Sampling

Back 19

 Easy to implement, but worst method of sampling

Front 20

Monetary Unit Sampling (MUS)

Back 20

Approach to variables sampling that uses attribute sampling methods to estimate monetary amounts

Front 21

Test Binary; Yes/No; Error/No error questions (Used to test the effectiveness of controls b/c it can estimate a rate of occurrence of control deviations in population)

Back 21

Attribute Sampling
Examples include:
1. Billing
2. Voucher processing
3. Payroll
4. Inventory pricing

Front 22

Examples of Random-based selections

Back 22

1. Random Sampling
2. Stratified random sampling
3. Monetary-unit sampling
4. Systematic sampling