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Defensible नमुना sizes, straight पासून SA 530.

Determine statistically valid नमुना sizes per SA 530, साठी attribute, systematic आणि monetary unit नमुना.

नमुना parameters
Population size5,000
50100,000
Expected error rate2%
0%10%
Tolerable error rate5%
1%15%
विश्वास पातळी
नमुना पद्धत
Required sample size
84
Sampling interval
60
Coverage rate
1.7%
शिफारस केलेली पद्धत
Random sampling requires 84 items selected using a random number generator from a population of 5,000. Each item has an equal probability of selection.
Quick reference: नमुना sizes द्वारे population
Population90%95%99%
100498087
50072176250
1,00077213358
5,00081253476
10K82260498
50K83267517
100K83268520
Based on expected error rate of 2% and tolerable error rate of 5% (attribute sampling).
SA 530 टीप
Per SA 530, professional judgement should supplement statistical calculations. Consider the nature of the population, stratification opportunities and specific engagement risks when determining final sample sizes.
Beyond नमुना

Move past नमुना - 100% च्या व्यवहार, automatically.

Coraa selects नमुने intelligently आणि चाचण्या every व्यवहार, flagging विसंगती before ते hit तुमचे कार्यपत्रिका.

पुढे

After तुम्ही've sized the नमुना, size the एंगेजमेंट.

मोफत चाचणी सुरू करावेळ अंदाज साधन वापरून पहा

How audit sampling under SA 530 works

SA 530 — "Audit Sampling" — provides the framework for designing, selecting, and evaluating audit samples. Sampling is the application of audit procedures to less than 100% of the items within a population such that all sampling units have an equal chance of selection, in order to provide the auditor with a reasonable basis on which to draw conclusions about the entire population.

Two broad approaches: statistical and non-statistical. Statistical sampling uses probability theory (Monetary Unit Sampling / MUS, Classical Variables Sampling) — sample size is calculated from confidence level, tolerable misstatement, and expected misstatement. Non-statistical sampling uses professional judgement but follows the same logical principles. Both must give all items an equal chance of selection.

Sample size is driven by: (a) the auditor's desired confidence level (typically 90-95%), (b) the tolerable misstatement (typically tied to performance materiality), (c) the expected misstatement in the population (from prior years or interim findings), and (d) the assessed risk of material misstatement. Higher risk → larger sample. Tests of controls follow attribute sampling (yes/no — control operated as designed); tests of details follow monetary sampling.

Worked example — substantive sample for trade receivables

A company has 3,500 trade receivable balances totaling ₹50 cr. Performance materiality is ₹40 lakh. Expected misstatement based on prior year is ₹5 lakh. Risk assessment is "moderate".

Inputs
Population value₹50 Cr
Population count3,500 balances
Performance materiality₹40 L
Expected misstatement₹5 L
Confidence level (1 - β)90% (β = 10%)
Risk factor2.31 (moderate)
Output
Sampling interval~₹15 L (₹40 L − ₹5 L) / 2.31
Sample size (MUS)~33 balances
Selection methodProbability-proportional-to-size
DocumentationFormula + seed value
Monetary Unit Sampling selects ~33 balances. The probability of selection is proportional to balance size — larger balances are more likely to be selected, focusing audit effort on monetary value. Document the formula, the seed value (for reproducibility), and the population. Any item ≥ sampling interval (₹15 L here) is automatically selected (key items).

Common mistakes

Treating "stratified" sampling as one bucket
Stratified sampling requires separate computation of sample size for each stratum based on its risk characteristics. The Total sample size is NOT the same as treating the population as one bucket. Common error: applying overall stratum count to a high-risk substratum.
Not projecting sample misstatements to population
SA 530 para 14 requires the auditor to project monetary misstatements found in the sample to the population. For MUS — ratio projection. For non-statistical — average misstatement × number of items in population (or proportional projection). Projected misstatement is what gets compared against tolerable misstatement.
Using haphazard selection instead of random / systematic
Haphazard selection (auditor picks without conscious bias) is acceptable for non-statistical sampling but is weaker than random or systematic. SA 530 paragraph A21 emphasises random selection methods. Document the selection method in WPs.
Failing to document the formula and seed
A reproducible sample is a defensible sample. Document: the formula (e.g., MUS with skip = population value / sample size), the seed value (random starting point), the population reference (e.g., trial balance as on X date), and the population total. Without this, a peer review or NFRA review cannot validate the procedure.

Frequently asked questions

What is audit sampling under SA 530?+
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 to draw conclusions about the entire population.
What is the difference between statistical and non-statistical sampling?+
Statistical sampling — uses probability theory (MUS, classical variables, attribute) to compute sample size and evaluate results with statistical confidence levels. Non-statistical — uses professional judgement to design the sample without statistical computation, but must follow the same principles of randomness and projection.
What is Monetary Unit Sampling (MUS)?+
A statistical sampling technique where each rupee in the population has an equal probability of selection. Larger-value balances are more likely to be selected (probability proportional to size). MUS is efficient for testing existence / valuation / cut-off of monetary balances — receivables, inventory, payables.
What is tolerable misstatement?+
The amount of misstatement in the population (or stratum) that the auditor is willing to accept and still conclude that the audit objective has been achieved. Usually set at or below performance materiality. Higher tolerable misstatement → smaller sample. Lower tolerable misstatement → larger sample.
How is sample size related to risk?+
Higher risk of material misstatement → larger sample required. The risk factor (1.6 for low, 2.31 for moderate, 3.0 for high) multiplies the sample size in MUS. The relationship is non-linear — doubling the risk does not double the sample, because the formula uses the natural log of (1 - confidence).
What is the difference between attribute and variable sampling?+
Attribute sampling — tests of controls (yes / no, did the control operate?). Sample size derived from expected deviation rate and tolerable deviation rate. Variable sampling — tests of details (how much is the balance worth?). Sample size derived from monetary measures (tolerable misstatement, expected misstatement).
How are sample results projected to the population?+
For MUS — projected misstatement = (misstatement in sample / book value of sampled items) × book value of population for that stratum. For non-statistical — proportional projection or judgemental projection. The projection plus an allowance for sampling risk gives the upper error bound, compared against tolerable misstatement.
When should I use 100% selection instead of sampling?+
When (a) the population consists of a small number of large-value items; (b) the items are individually material (any single misstatement could be material); (c) tests of controls are not feasible; (d) when the population is small and 100% testing is more efficient than sampling. SA 530 para 5 acknowledges these cases.

Authoritative sources

SA 530 — Audit Sampling (ICAI AASB) — Read alongside SA 315 (risk assessment), SA 330 (responses), and SA 450 (evaluation of misstatements). ICAI Guidance Note on Audit Sampling provides illustrative tables and examples.
Always confirm against the latest version of the source. Regulations evolve and amendments are common.
Related calculators
SA 530 page →Materiality Calculator →Audit Risk Scorer →Time Estimator →
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Last reviewed: 2026-05-28 · For informational purposes only — not professional advice.