Calculate Sample Size for Power Analysis
Introduction & Importance
Calculating sample size for power analysis is crucial in ensuring your study has enough participants to detect an effect if there is one. It helps you plan your research, allocate resources, and avoid underpowered or overpowered studies.
How to Use This Calculator
- Enter the effect size, significance level (α), power, and standard deviation.
- Click “Calculate”.
- View the results and chart below.
Formula & Methodology
The formula used in this calculator is based on Cohen’s power analysis:
n = (Z_α/2 + Z_β)^2 * σ^2 / d^2
Where:
nis the sample size,Z_α/2is the critical value of the normal distribution at the α/2 level,Z_βis the critical value of the normal distribution at the β level,σis the standard deviation,dis the effect size.
Real-World Examples
Data & Statistics
| Test | Small Effect | Medium Effect | Large Effect |
|---|---|---|---|
| t-test | 0.2 | 0.5 | 0.8 |
| F-test | 0.1 | 0.25 | 0.4 |
Expert Tips
- Consider using a power of 0.8 or 0.9 for your study.
- Be aware that increasing power requires a larger sample size.
- Always round up your calculated sample size to ensure you have enough participants.
Interactive FAQ
What is power in statistics?
Power is the probability that a test will reject the null hypothesis when the alternative hypothesis is true.