## Audit Sampling (SA 530)

### Definition

Application of audit procedures to less than 100% of items within a population of audit relevance such that:

All sampling units have a chance of selection
Results provide a reasonable basis to draw conclusions about the entire population

### Sampling Risk

Risk that the auditor's conclusion based on a sample differs from the conclusion that would have been reached if the entire population were subjected to the same audit procedure.

#### Two Types of Erroneous Conclusions

	Tests of Controls	Tests of Details	Consequence
Type I (Under-reliance / Inefficiency)	Conclude controls are less effective than they actually are	Conclude material misstatement exists when it doesn't	Auditor does more work than necessary → Additional work
Type II (Over-reliance / Incorrect Opinion)	Conclude controls are more effective than they actually are	Conclude material misstatement does NOT exist when it does	Inappropriate audit opinion

> Critical: Type II error is far more serious because it directly compromises audit quality and results in an incorrect opinion being issued.

### Non-Sampling Risk

Risk of erroneous conclusions for any reason NOT related to sampling, for example:

Using an inappropriate audit procedure
Misinterpreting evidence obtained
Failing to recognize a misstatement or deviation

> Non-sampling risk cannot be reduced by increasing sample size. It is managed through proper planning, supervision, and professional care.

### Statistical vs. Non-Statistical Sampling

Statistical sampling requires BOTH:

1. Random selection of sample items (so every item has a known, non-zero chance of selection)

2. Probability theory to evaluate results (including quantification of sampling risk)

Any approach lacking either characteristic is non-statistical sampling.

> Both approaches, when properly applied, can provide sufficient appropriate audit evidence. The advantage of statistical sampling is the ability to measure sampling risk mathematically.

Worked example

### Example 1

Type II error (dangerous): The auditor selects 50 invoices from 5,000 and finds no errors. He concludes there is no material misstatement in accounts payable. However, 200 invoices were recorded at inflated amounts (not caught in the sample). The auditor issues an unmodified opinion on materially misstated FS – this is a Type II sampling error leading to an inappropriate audit opinion.

### Example 2

Type I error (wasteful): An auditor tests internal controls over purchase approvals and, from his sample, incorrectly concludes the controls are unreliable (operating at 15% deviation rate). He extends substantive testing significantly. In reality, the control deviation rate was only 2%. The excess work is a Type I error consequence – inefficiency, but no damage to opinion quality.

### Example 3

Non-sampling risk example: An auditor selects the entire population (100%) of journal entries above ₹10 lakhs for review. Despite full coverage (no sampling), he misclassifies a fictitious entry as legitimate because he misreads the supporting document. This error is non-sampling risk – it exists regardless of sample size.

⚠️ Common exam mistakes

Reversing Type I and Type II errors: remember Type II (over-reliance) leads to the WRONG opinion and is more dangerous; Type I (under-reliance) leads to more work but a correct opinion
Thinking non-sampling risk decreases as sample size increases – non-sampling risk is entirely independent of sample size; it arises from poor procedures, judgment errors, or oversight
Assuming statistical sampling is always superior to non-statistical sampling – both can yield SAAE; statistical sampling only adds the ability to quantify sampling risk mathematically
Forgetting that 'all sampling units must have a chance of selection' is a fundamental requirement – auditor selection methods that systematically exclude certain items do not qualify as sampling

Bare-Act text Definition – Audit Sampling · SA 530 – Audit Sampling (ICAI) · click to expand

Audit sampling means the application of audit procedures to less than 100% of items within a population of audit relevance such that all sampling units have a chance of selection in order to provide the auditor with a reasonable basis on which to draw conclusions about the entire population.

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Sampling Risk, Non-Sampling Risk, and Statistical vs Non-Statistical Sampling

Worked example

⚠️ Common exam mistakes