Term
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Definition
| Because examining 100% of accounts is too costly and not a timely action. An auditor needs an efficient and effective way to reach a judgment about a population that is too large to examine completely. |
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Term
| Timeline/Trends in Sampling |
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Definition
1970s/80s - Stat sampling tech's for auditing were refined and applied widely
1990's - competitive fee pressures led to lower sample sizes and cutting corners
SOX - stat sampling rebounded in importance |
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Term
| Pros and Cons of Nonstatistical Sampling |
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Definition
Pros: doesn't require add. software, can be based on auditor's prior expectations about errors, less time to plan, select and evaluate the sample.
Con - requires audit judgment to determine app. sample size, doesn't provide an objective way to control sapling risk |
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Term
| Pros and Cons of Statistical Sampling |
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Definition
Pros - Helps the auditor design an efficient sample, measure sufficiency, evaluate results by providing an objective measure of sampling risk, efficiencies through computerized selection, sample inferences based on stat theory.
Cons - Requires knowledge of stat sampling methods or special sampling software, training costs, requires definitions of acceptable risk and sample objectives to be made in advance. |
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Term
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Definition
Population - all of the sampling units make up the population
Sample - the individual items to be tested
Duh |
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Term
| Attribute Sampling b. Substantive sampling of balances |
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Definition
Attribute - commonly used to test Internal Controls
Substantive - Direct test on accounts and F.S. |
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Term
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Definition
| The risk of concluding that the controls are effective when they are not effective. Often set the same as audit risk because the auditor's assessment of internal controls determines the nature and extent of other testing. The auditor tests only significant controls. |
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Term
| Risk of incorrect acceptance vs Risk of Incorrect rejection |
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Definition
Incorrect Acceptance - offers clean opinion when there is a misstatement - MOST SERIOUS
Incorrect Rejection - Saying there is a mistake but there isn't |
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Term
| How is Statistical Intuition Poor? |
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Definition
| Sampling risk goes DOWN as the sample size goes UP and ALL people tend to have a poor intuitive feel for this relationship....ex: 40/50 students and 4/5 students usually mean the same thing to people where as they have completely different confidence levels in terms of being representative of a population. |
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Term
| Auditors intuition for sampling... |
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Definition
| tend to select sample sizes that are too small to provide the desired level of assurance because of costs and meeting budgets. Therefore - they should used software to determine sample sizes. |
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Term
| Statistical Fallacy and Fact |
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Definition
Fallacy - Just cover the biggest items and skip the rest.. OBVIOUSLY NOT TRUE!
FACT - It is a good idea to test individually significant items, but a valid sample should include a representative CROSS-SECTION of ALL items - send confirmations to some customers of the client having low balances too (a lot of low balances can add up to a lot) |
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Term
| Attribute Sampling asks What kind of Questions? |
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Definition
"Yes/No" - does the control work, or not? (IC Testing)
EX/ Was Authorization documented? Were customers billed before goods were shipped? Was there compliance laws, regulations, or policies? |
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Term
| What helped Attribute sampling increase in importance again? |
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Definition
| Implementation of SOX 404 and PCAOB Auditing Standards. |
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Term
| 3 Parameters needed for an effective attribute sample: |
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Definition
1. Sampling risk (risk of concluding controls are effective when they aren't AND risk of assessing control risk too low) - Risk that it doesn't represent population.
2. Tolerable failure Rate "Tolerable Deviation Rate"
3. Expected Failure rate - How frequently do you expect to see control fail? |
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Term
| Tolerable failure/deviation rate: |
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Definition
| The level at which the control's failure to operate would change the auditor's planned assessment of control risk in performing tests of account balances. Must be set in advance in order to determine sample size. |
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Term
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Definition
| It is likely that there are times a control may failr or be bypassed - if people are in a hurry or careless or not competent. An auditor has evidence on the rate at which a particular control fails based on past experience. |
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Term
| Attribute Sample Size Tables |
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Definition
there is 5% and 10% charts for sampling risk
Expected deviation rate is the range of numbers vertical on the left...
The tolerable deviation rate is the percentage at the top going horizontal
the sample size is the number in the chart
The (#) is the number of times you should expect to see it fail |
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Term
| When looking for upper bound of the deviation rate.. |
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Definition
| USE the attribute estimation sample evaluation table... Find the sample size on the left vertical column.. (but sure to look at the table with the right confidence level/sample size) then find the number of control deviations (fails) found.. and then you will find the percentage. EX - you will then be 95% confident that the control won't fail ___% of the the time. |
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Term
| How you know if the deviation rate is acceptable/Unacceptable - |
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Definition
| Unacceptable - if the upper bound exceeds maximum tolerable deviation rate. Auditors should then test a compensation control or adjust the nature, timing, and/or extent of the related substantive testing of the F.S. accts as the controls aren't working at a satisfactory level. |
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Term
| Problems with Isolated Exceptions in sample testing |
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Definition
1. It can be tempting to rationalize away isolated errors in a sample
2. SAMPLING ERRORS MUST BE PROJECTED TO THE POPULATION
3. Auditor certainly should investigate reasons for detected errors (qualitative evaluation) |
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Term
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Definition
| When control failures are found, they should be analyzed qualitatively as well as quantitatively - auditor should try to determine whether the failures were 1) Intentional/Unintentional 2) Random/Systematic 3) Had a direct dollar effect on the account balance 4) were of such magnitude that a material dollar amount of errors could occur and not be detected. |
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Term
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Definition
| Every item in the population has an equal chance of being selected. Unpredictable is desired. |
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Term
| Systematic Sample with Random Start |
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Definition
| Selecting groups of students from a class - take every 5th student in the class (usually has a pattern) |
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Term
| Probability-proportional-to-size (PPS)/monetary unit Sampling (MUS) |
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Definition
| Gives all clients the chance of being selected, BUT it is more likely a bigger client is chosen. |
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Term
| 3 Types of Stat Sample Selection Methods |
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Definition
1. True Random Sample
2. Systematic sample with random Start
3. PPS/MUS |
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Term
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Definition
| Does NOT measure or control for sampling risk! But, can project detected misstatements. Does not have statistical confidence, test samples from all populations. Test all sig. items and other randomly selected items with particular characteristics. |
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Term
| Example of projecting nonstatistical results.. |
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Definition
| take the amount of misstatements of the sample for a category.. divide by the total amount tested in the sample... and then multiply that number by the total amount for that category in the populations - this gives you the projected total misstatement! |
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Term
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Definition
| IR (inherent Risk) * CR (chance that internal controls won't work and auditors will miss it) * DR (detection risk |
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