AUD 5 - Audit Sampling Flashcards
Audit Sampling
Sampling refers to the examination of less than 100% of a population & using the results as a basis for drawing a general conclusion on the entire population.
Nonsampling Risk
vs.
Sampling Risk (2)
Nonsampling Risk - The risk that human error will lead to drawing the wrong conclusion. (Human error, misinterpreting audit test results, not recognizing misstatments in documents audited)
Sampling Risk - The risk of drawing the wrong conclusion based on a bad sample. Two types of sampling risks:
-
Type I - Efficiency Error
- Population is OKAY, but sample is BAD
- Underrely on I/C = High RMM assessment
- Incorrectly Reject an accont balance for substantive testing purposes.
- Population is OKAY, but sample is BAD
-
Type II - Less Effectiveness
- Population is BAD, but sample is OKAY
- Overrely on I/C = Low RMM assessment
- Incorrectly Accept an account balance for substantive testing
- Population is BAD, but sample is OKAY
There are two times when audit sampling are used, when are they?
- During the internal control phase of the audit, the auditor will perform test of controls on a sample basis to determine the operating effectiveness of controls they plan to rely on. (called Attribute Sampling)
- During the substantive testing phase of the audit, auditor will perform test of details details (I-CORRIIA) of transactions , accounts & disclosures on a sample basis to obtain sufficient appropriate audit evidence to support managenent assertions. (called Variable Estimation Sampling)
What are two ways sample size is determined?
Statistical & Non-statistical (Judgemental)
Statistical Sampling - refers to the use of quantitative measures of the auditor s taking in the use of sampling. Formulas** are **used** to **determine** the **sample size necessary.
Nonstatistical Sampling - (Judgemental Sampling) a method of sampling under which the auditor applies judgement to determine sample size & to interpret sample results.
- Auditors using non-statistical sampling tends to overestimate the needed sample size. Therefore, audit tends to be inefficent despite being effective.
Sampling Risk Summary
(Internal Ctrl vs. Substantive Testing)
Internal Control: Attribute Sampling (Characteristics)
- Assessing RMM HIGH (under rely) = Inefficient
- Assessing RMM LOW (over rely) = Ineffective
Substantive Testing: Variable Sampling ($ Amounts)
- Incorrect Rejection = Inefficient
- Incorrect Acceptance = Ineffective
Attribute Sampling
(two risks,sample size,evaluation)
- Attribute sampling is for Internal Controls
-
Two Risks
- Assessing RMM too Low = Audit ineffective (T2)
- Assessing RMM too High = Audit inefficient (T1)
-
Factors affecting Sample Size (Tested)
- Tolerable Rate - Inverse effect
- Expected Error Rate (Deviation) - Direct effect
- Acceptable Risk (Allowance) = Inverse effect
- Population Size = Little or No effect
-
Evaluation of Sample Results
- Calculate Sample Deviation Rate
- Deviation Rate = # of errors / sample size
- Calculate Maximum Deviation Rate (MDR)
- MDR = Sample Deviation + Allowance
- Compare Maximum Deviation Rate vs. Tolerable Rate
- Maximum Deviation Rate must NOT exceed Tolerable rate or else Auditor must modify planned reliance
- Calculate Sample Deviation Rate
Attribute Sampling
What are the two risks associated with Attribute Sampling?
- Attribute sampling is for Internal Controls
-
Two Risks
- Assessing RMM too Low = Audit ineffective (T2)
- Assessing RMM too High = Audit inefficient (T1)
Attribute Sampling
What are factors affecting sample size? (TEA)
- Attribute sampling is for Internal Controls
-
Factors affecting Sample Size (Tested)
- Tolerable Rate - Inverse effect
- Expected Error Rate (Deviation) - Direct effect
- Acceptable Risk (Allowance) = Inverse effect
- Population Size = Little or No effect
Attribute Sampling
How to evaluate sample results?
- Attribute sampling is for Internal Controls
-
Evaluation of Sample Results
- Calculate Sample Deviation Rate
- Deviation Rate = # of errors / sample size
- Calculate Maximum Deviation Rate (MDR)
- MDR = Sample Deviation + Allowance
- Compare Maximum Deviation Rate vs. Tolerable Rate
- Maximum Deviation Rate must NOT exceed Tolerable rate or else Auditor must modify planned reliance
- Calculate Sample Deviation Rate
Attribute Sampling
Sampling Methologies (4)
(Random Number,Systemic,Haphazzard,Block)
A sample, by definition, should be representative of the population under consideration. For a sampling method to be valid, all items in the population should have an equal opportunity to be selected. Such methods include:
- Random-Number Sampling - numbered documents or transactions are selected through the use of random number tables or computer software.
- Systemic Sampling - every “Nth” item is selected from a randomly-distributed population from a randomly-selected starting point.
- Haphazard Sampling - a sample consisting of units selected without any conscious bias - again assuming the random distribution of the population.
- Block Sampling - a sample consisting of contiguous units, example: a selection of three blocks of ten vouchers each.
Variable Sampling
What are the two risks?
What affects Sample Size? TAPES
- Substantive Testing - Test of Details
-
Two Risks:
- Incorrect Acceptance = Audit Ineffective
- Incorrect Rejection = Audit Inefficient
-
Factors affecting Sample Size (TESTED)
- Tolerable misstatement - Inverse
- Accetance Risk - Inverse
- Population Size - Direct
- Expected Misstatement - Direct
- Standard Deviation - Direct
- RMM - Direct
Variable Sampling & Sample Size Formula
What makes sample size increase or deacrease? TAPES
TESTED
To be more Precise, Sample Size (SS) will need to increase.
- Tolerable Rate = Inverse
- Acceptable Risk = Inverse
- Population Size = Direct (very little)
- Expected Misstatements/Errors = Direct
- Standard Deviation = Direct
- Risk of Material Misstatements = Direct
SS = (Std Deviation + Reliability + Population) / Allowance
Types of Classical Variables Sampling (4)
(MPU,difference estimation,ratio estimation,stratified)
-
Mean-per-Unit
- MPU = Average Actual Audit Results x Total Population
-
Difference Estimation
- DE = ((Actual - Sample) x Total Population) + Base
-
Ratio Estimation
- RE = Avg Ratio x Population
- The use of the ratio estimation sampling technique is most effective when the calculated audit amounts are approximately proportional to the client’s book amounts.
-
Stratified Sampling
- Population is divided into groups
- Sample size is drawn from each group
Probability Proportional to Size Sampling (PPS)
PPS - A sampling plan under which items exceeding a certain dollar amount (sampling interval) are always included in a sample &, for remaining items, the greater the amount, the greater the likelihood of being included in the sample.
Calculations Needed:
-
Sampling Interval (SI): 2 Ways to Calculate
- SI = Tolerable Misstmt / Reliability Factor (from Table)
- SI = Population Amount / Sample Size
- Sample Size = Population Amount / Sampling Interval
To Determine Projected Misstatements (PM):
- Misstatement = Book (Recorded) Amt - Audited Amt
- Tainting Factor (TF%) = Misstatement / Book Amount
- Projected Misstatements (PM) - Audit Adjustment
- If SI > Book (Recorded) Amount
- PM = TF% * SI
- If SI < Book (Recorded) Amount
- PM = Book Amount - Audited Amount
- If SI > Book (Recorded) Amount
PPS Advantages (4)
vs.
PPS Disadvantages (2)
Advantages of PPS over classical variable are:
- Standard deviation is NOT needed
- Stratifies sample automatically
- Smaller sample usually results in few errors expected
- Able to start sampling without having entire population available or finished
Disadvantages of PPS over classical variable are:
- NOT Useful to detect understatement
- Zero & negative balances require special handling
