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Microlesson · 5-min read

SA 530 – Audit Sampling: Overview, Statistical vs Non-Statistical Sampling

## Audit Sampling – Overview and Approaches (SA 530)

### 1. What is Audit Sampling?

Audit sampling means applying audit procedures to less than 100% of items in a population so that all sampling units have a chance of selection, and the auditor can draw a conclusion about the entire population.

> The sample must be representative of the population – every item should have an equal (or known) chance of being selected.

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### 2. Where Sampling is Applied

Procedure TypeWhat it TestsWhat it Identifies
Test of ControlsInternal controlsDeviations in control operation
Substantive Testing (Test of Details)Account balances / transactionsMisstatements (amount, classification, presentation)

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### 3. Key Definitions

  • Population – The entire set of data from which the auditor wishes to sample (must be complete and appropriate for the audit objective)
  • Sampling Unit – The individual items that make up the population (e.g., individual debtor accounts within the debtors ledger)

> Population completeness matters: If testing existence of credit sales, the population should be credit sales invoices only – cash sales must be excluded.

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### 4. Two Approaches to Sampling

#### A. Statistical Sampling

  • Based on probability theory and random selection
  • Each item has an equal and known chance of being selected
  • Auditor can quantify sampling risk and measure confidence mathematically
  • Software tools are used to determine minimum sample size given ROMM and desired confidence level
ROMM LevelConfidence Level RequiredEffect on Sample Size
Low~95%Smaller sample
Medium~97–98%Moderate sample
High~99%Larger sample

#### B. Non-Statistical Sampling

  • Based on auditor's judgment and prior experience
  • No mathematical measurement of sampling risk
  • Example: Auditor selects the top 20 debtor accounts based on balance size
  • Sampling risk cannot be quantified

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### 5. Population Characteristics

A reliable population must satisfy two qualities:

QualityMeaning
AppropriatenessPopulation matches the audit objective (right data)
CompletenessNo items are missing (e.g., no invoice is absent from the listing)

> External evidence (e.g., bank statements, supplier invoices) is more reliable than internal evidence as a source for sampling.

Worked example

### Example 1

Sampling for debtor existence: Auditor wants to test existence of debtors. Population = list of debtors at year-end. Sampling unit = individual debtor account. Statistical sampling is used with 99% confidence level (ROMM is high). Software calculates minimum sample size of 60 accounts. Each account has equal chance of selection via random number generation.

### Example 2

Non-statistical sampling – top 20 debtors: Auditor reviews the aged debtors list and selects the 20 largest balances (₹5 lakh and above) for confirmation. This covers 70% of the total debtors balance by value. Though sampling risk cannot be quantified, the auditor's judgment targets the highest-risk items.

### Example 3

Population completeness – credit sales only: Company has 5,000 sales invoices (4,200 credit, 800 cash). Auditor is testing existence of credit sales. Population = 4,200 credit invoices only. Including the 800 cash invoices would make the population inappropriate for the objective.

⚠️ Common exam mistakes

  • Defining the population incorrectly – e.g., including cash sales when testing credit sales existence; the population must match the audit assertion.
  • Confusing statistical and non-statistical sampling as 'better' vs 'worse' – both are acceptable under SA 530; the difference is whether sampling risk can be quantified.
  • Thinking that non-statistical sampling is always biased – it is judgment-based, not random, but it is still a valid approach when applied with professional care.
  • Using a low confidence level for high-ROMM areas – when ROMM is high, the auditor must use a higher confidence level (e.g., 99%), which increases sample size.
Reference: — SA 530 – Audit Sampling (ICAI)
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