Sample Size Calculator - Free Statistical Sample Size Calculator
Sample Size Calculator
Calculate the required sample size for your research study, survey, or experiment with specified confidence levels and margins of error.
Sample Size for Population Proportion
Use 50% for maximum variability
Leave blank for large/infinite population
How to use this calculator
📊 How to Use This Calculator
- Choose your calculation type: proportion, mean, or group comparison
- Select your desired confidence level or significance level
- Enter the margin of error you can tolerate
- Provide population parameters (standard deviation, expected proportion)
- Click calculate to get your required sample size
📐 Sample Size Formulas
For Population Proportion
n = (Z² × p × (1-p)) / E²
Where: Z = z-score, p = expected proportion, E = margin of error
For Population Mean
n = (Z² × σ²) / E²
Where: σ = standard deviation, E = margin of error
Finite Population Correction
n_adjusted = n / (1 + (n-1)/N)
Where: N = population size
🌟 Effect Size Guidelines
Small (d = 0.2)
Subtle differences, requires careful measurement
Medium (d = 0.5)
Noticeable differences, visible to careful observer
Large (d = 0.8)
Obvious differences, easily noticeable
💡 Pro Tips
- • Use 50% for expected proportion when you have no prior information (most conservative)
- • Add 10-20% to your calculated sample size to account for non-response
- • For pilot studies, use n = 30 as a rule of thumb
- • Consider stratified sampling for heterogeneous populations
- • Ensure your sample size is adequate for planned subgroup analyses
- • Document your sample size justification for research proposals
⚠️ Common Mistakes to Avoid
- • Using too small a sample size (underpowered study)
- • Forgetting to account for clustering effects in cluster samples
- • Not planning for dropouts and missing data
- • Using infinite population formulas for small populations
- • Ignoring the need for larger samples in subgroup analyses
- • Confusing standard error with standard deviation
About this calculator
Calculate the required sample size for surveys, experiments, and research studies. Determine statistical power and confidence levels.
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