Sample Size Calculator
Determine the ideal sample size for surveys and research studies
Total number of people in your target population (use 0 or very large number for unknown/infinite)
How confident you want to be in your results (95% is standard)
Acceptable range of error in your results (±5% is typical)
Estimated percentage with the characteristic (use 50% for maximum sample size/most conservative)
respondents needed
n = (Z² × p × (1-p)) / E²
Where: n = sample size, Z = Z-score, p = proportion, E = margin of error
Adjusted for finite population using: n / (1 + (n-1)/N)
Sample size calculation determines how many people you need to survey to get statistically valid results. The right sample size ensures your findings accurately represent the entire population while minimizing cost and effort.
Key Factors
- Confidence Level: How certain you want to be (95% = 19 out of 20 times results will fall within margin of error)
- Margin of Error: Acceptable range of uncertainty (±5% means results could vary by 5 percentage points either way)
- Population Size: Total number in target group (larger populations don't require proportionally larger samples)
- Proportion: Expected percentage with characteristic (use 50% for maximum sample size when unknown)
Important Principles
- • Larger samples = more accurate but more expensive
- • Higher confidence levels require larger samples
- • Smaller margins of error require larger samples
- • Random sampling is crucial for validity