Sample Size Calculator
Work out how many people or items you need to survey to reach a target confidence level and margin of error.
Your results
Enter a population size above zero to apply the finite population correction for a known, limited population.
Calculation breakdown
- Base sample size
- n₀ = z² × p × (1 − p) / e²
- Finite population correction
- n = n₀ / (1 + (n₀ − 1) / N)
Worked example
To survey a suburb of 5,000 residents with 95% confidence and a 5% margin of error, assuming the most conservative 50% expected proportion, you would need to survey about 357 people.
Assumptions
- Uses the most conservative 50% expected proportion by default; a more accurate estimate of the true proportion can reduce the required sample size.
- Assumes simple random sampling; more complex sampling designs (e.g. stratified) may need a different formula.
How this calculator works
Enter your desired confidence level, margin of error and expected proportion, plus an optional population size. The calculator returns the minimum sample size needed, applying a finite population correction where a population size is given.
Frequently asked questions
Why is 50% used as the default expected proportion?
50% gives the most conservative (largest) required sample size when the true proportion is unknown, so it's a safe default.
What happens if I enter a population size?
A finite population correction is applied, which can reduce the required sample size for smaller, known populations.
What's a typical margin of error for a survey?
Many public surveys target a margin of error around 3–5%, though the right choice depends on how precise your results need to be.