Sampling - Audit Exam 3

Front 1

Concepts of Sampling

Back 1

Sampling Risk

Sampling Error

Nonsampling Risk

Tolerable Misstatement/Dev rate

Expected Misstatement/Dev Rate

Allowance for sampling risk

Confiedence level

Front 2

Sampling Risk

Back 2

Risk sample does not represent the pop

Type I and Type II Errors

Front 3

Explain the types of errors

Back 3

Type I: Incorrect Rejection - CR too low

Type II: Incorrect acceptance - CR too high

Front 4

Sampling Error

Back 4

Difference between actual error rate or misstatement amt in the pop

Front 5

Nonsampling risk

Back 5

Auditor might select wrong procedure, might misapply correct procedure, or misinterpret results

Front 6

Two types of sampling

Back 6

Statistical - Uses statistical theory, less judgement, known sampling risk

Nonstateistical - Sampling risk estimated, more judgement, and based on theory & firm guidance

Front 7

Control testing

Back 7

To determine if dev rate is too high

Generally statistical

Uses computers

Front 8

Substantive testing

Back 8

Misstatement/acct value is too high

Generally nonstatistical

Requires judgement

Careful of small sample sizes

Consider sampling risk
Haphazard selecting most common

Front 9

Samplers must address

Back 9

How many/Sample Size

Which ones/Sampling method

How do I interpret results?

Front 10

How many/Sampling Size

Back 10

Population Size

Desired confidence level

Margin of error/allowance for sampling risk

Front 11

Confidence level

Back 11

How confident do I want to be that im right?

Larger sample = more confidence

Front 12

Allowance for sampling risk

Back 12

Tolerable Problems - Expected problems

Smaller difference = more precise

Front 13

Expected problems

Back 13

Can be based on historical data

Front 14

Expected Misstatement/Dev rate

Front 15

Which items

Back 15

Statistical Sampling = Every item has equal chance of being selected

Nonstatisical Sampling = Random, Systematic, Haphazard, Judgemental

Front 16

4 step approach to Interpreting results

Back 16

1. Sample in misstatement/deviation rate

2.Project to population

3. Consider sampling risk

4. Plausible vs tolerable (want a <)

Front 17

Attribute Sampling

Back 17

IC testing

Must define attribute being tested with support

Small Sample size

Low error rate(TE 5%, Expected error 0)

Provides existence question!

Front 18

Formula

Back 18

(Population BV/Margin of error)*Reliability factor

Front 19

Steps for Sampling

Back 19

1. determine Test obj

2.Define: pop, missstatemen/deviation

3.Determine sample size

4. Select sample items

5. Preform auditing procedure

6. Calc projected misstatement

7. Conclude

Front 20

Calculating results two methods

Back 20

Ratio Projection

Difference Projection

Front 21

Ratio Projection

Back 21

Take Ratio of misstatement and apply to population

Front 22

Difference Projection

Back 22

Average misstatement applied to population