#1988 · Legal & Compliance Tool

Trademark Filing Audit Sample Size Calculator

Estimate a statistically based random audit sample for trademark filing work. Adjust the operational assumptions to reflect your matter, policy, jurisdiction, and service providers, then use the supporting results to document a planning scenario. This tool provides an estimate and does not determine legal obligations or outcomes.

Calculator

Population and assurance assumptions
records
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How to use this calculator

  1. Enter the workload, date, cost, or risk assumptions shown in the calculator.
  2. Use values from your current policy, matter records, fee schedules, or documented planning assumptions.
  3. Select Calculate and review the main result plus each supporting metric.
  4. Change one uncertain input at a time to compare scenarios, then confirm the result with the responsible legal or compliance professional.

Formula

Initial sample n₀ = z²p(1−p) ÷ e². Finite-population sample n = n₀ ÷ [1 + (n₀−1)/N], rounded up. z is derived from the selected two-sided confidence level.

What the result means

The result estimates a statistically based random sample for measuring an exception proportion at the chosen confidence and precision.

Random sampling does not replace risk-based selection. Use the most conservative expected rate of 50% when no defensible prior estimate exists.

Example calculation

For 5,000 records, 95% confidence, a 5% margin, and a 10% expected exception rate, the finite-population sample is approximately 135 records.

Tips for better results

  • Keep the source and date for each assumption in the matter file.
  • Run low, expected, and high scenarios where an input is uncertain.
  • Separate materially different populations or work types instead of masking them in one average.
  • Recalculate when volume, staffing, fees, deadlines, or legal status changes.
  • Have the responsible professional approve any action based on the estimate.

Frequently asked questions

Why does the trademark filing sample use the expected exception rate?

The expected proportion affects variance and therefore sample size. If no reliable estimate exists, 50% produces the most conservative sample.

Does a larger population always require a much larger sample?

Not after the population becomes large relative to the initial sample. The finite-population correction has less effect as population size grows.

Should I round the audit sample down?

No. The calculated sample is rounded up so the selected precision is not weakened by rounding.

Can this sample prove there are no exceptions?

No. It estimates an exception proportion within a margin of error; a zero-finding assurance design requires a different approach.

Must every record have an equal chance of selection?

For the stated random-sample interpretation, use a documented random method. Risk-based additions may be reviewed separately.

Inputs and units

Input groupHow it is used
Population and assurance assumptionsDefines the core planning scenario.
Rates and allowancesAdjusts effort, precision, cost, timing, or exposure.
Supporting resultsShows intermediate values for review and documentation.

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