Set Your Parameters
Enter your population size, desired confidence level, and margin of error. Adjust design effect for cluster sampling.
A straightforward approach to sample size calculation using standard statistical formulas.
Enter your population size, desired confidence level, and margin of error. Adjust design effect for cluster sampling.
The calculator applies Cochran's formula with finite population correction, then adjusts for design effect and non-response.
Save your calculation for proposals, or compare sample sizes across different margins of error.
Calculate the sample size for M&E surveys and evaluations, or find your margin of error for a fixed sample.
Total number of individuals in the target population
Higher confidence requires a larger sample
Use 50% if unknown (produces the most conservative estimate)
1.0 for simple random sampling, 1.5-2.0 typical for cluster sampling
Accounts for respondents who cannot be reached or refuse to participate
Required Sample Size
412
respondents needed
| Margin of Error | Sample Size |
|---|---|
| 4% | 630 |
| 5% (selected) | 412 |
| 6% | 289 |
This calculator uses Cochran's formula for sample size determination, which is the standard approach for survey research:
n₀ = (Z² × p × (1-p)) / e²
Where Z is the z-score for your confidence level (1.96 for 95%), p is the expected proportion, and e is the margin of error. For finite populations, a correction factor is applied:
n = n₀ / (1 + (n₀ - 1) / N)
The final sample is then adjusted for design effect (DEFF) when using cluster or stratified sampling, and for expected non-response:
n_final = (n × DEFF) / (1 - non-response rate)
Our advisory services help M&E teams design sampling approaches that balance rigor with practical constraints.