Sample Size Calculator

About the Sample Size Calculator

Sample size is one of the most critical decisions in any research study or survey design. Too small a sample produces unreliable results; too large wastes resources. Our sample size calculator determines the minimum sample needed to achieve your desired margin of error and confidence level, whether you are surveying a large population or testing two treatments in a clinical trial.

How It Works

For estimating a population proportion: n = (z*²× p × (1−p)) / E², where z* is the critical value for your confidence level (1.96 for 95%), p is estimated proportion (use 0.5 if unknown for maximum sample size), and E is the desired margin of error. For a 95% CI with ±5% margin of error on an unknown proportion: n = (1.96² × 0.5 × 0.5) / 0.05² = 384.16 ≈ 385 respondents.

Tips & Best Practices

• ✓For finite populations, apply the finite population correction: n_adj = n / (1 + (n−1)/N).
• ✓50% assumed proportion gives the most conservative (largest) sample size estimate.
• ✓Increasing confidence from 95% to 99% requires sample size to increase by 70%.
• ✓Halving your margin of error quadruples the required sample size.
• ✓Account for expected non-response by dividing target n by expected response rate.

Who Uses This Calculator

Market researchers designing customer satisfaction surveys, clinical researchers planning trials with sufficient power, quality control teams sampling production batches, political pollsters, and A/B testers calculating experiment duration all use sample size calculations as a prerequisite to data collection.