Audit Sample Size Calculator
Find the sample size for zero-defects attribute sampling.
How the audit sample size formula works
This calculator finds the sample size needed for zero-expected-errors attribute sampling — the standard approach used in internal audit and compliance testing when you plan to test a sample and want a defined confidence level that the true error rate is below your tolerable threshold, assuming you find no errors.
Enter your desired confidence level and the maximum tolerable error rate for the population. The calculator returns the required sample size.
This is the exact solution to the standard statistical question: if the sample is clean (zero errors found), how large does it need to be for you to be confident the true error rate is below your threshold? If errors ARE found in your actual sample, this formula alone no longer applies — a fuller statistical sampling plan is needed.
The formula
n = ln(1 − Confidence) ÷ ln(1 − Tolerable error rate)
This is the exact closed-form solution derived from the probability of finding zero errors in a sample of size n, when the true error rate equals your tolerable rate: (1 − tolerable rate)ⁿ ≤ (1 − confidence).
Worked example
95% confidence, 5% tolerable error rate
n = ln(1 − 0.95) ÷ ln(1 − 0.05) = ln(0.05) ÷ ln(0.95) ≈ 58.4, rounded up to 59.
Frequently asked questions
What if I find one or more errors in my sample?
This zero-errors formula no longer directly applies — finding any errors typically requires either expanding the sample or using a fuller statistical sampling table (e.g. Poisson-based tables with a built-in error allowance) to draw a valid conclusion.
What confidence level is standard for audits?
95% is common for many internal audit and compliance testing programs, though the right level depends on the risk and materiality of what you're testing.
Is this the same as a survey sample size calculation?
No — this answers a different question ("how large a sample proves the error rate is below X, given zero errors found") than the Sample Size Calculator (which estimates a proportion with a margin of error). Use whichever matches your actual question.
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