Power Analysis Calculator - Sample Size
Calculate statistical power, required sample size, effect size, and significance level for hypothesis testing. Essential for research design, clinical trials, A/B test planning, and survey methodology. Supports t-tests, chi-square, ANOVA, and correlation tests.
Power Analysis (Cohen)
n ≈ 2 × (Zα/2 + Zβ)² × σ² / d²Variables:
- nSample size per groupSample size per group
- ZαZ-score for alpha (1.96 for α=0.05)Z-score for alpha (1.96 for α=0.05)
- ZβZ-score for power (0.84 for power=0.8)Z-score for power (0.84 for power=0.8)
- σPopulation standard deviationPopulation standard deviation
- dEffect size (Cohen's d)Effect size (Cohen's d)
How to Use the KalkuLab Power Analysis Calculator
- 1
Enter Effect Size
Enter Cohen's d or expected effect size.
- 2
Set Alpha and Power
Set significance level (α, usually 0.05) and desired power (usually 0.80).
- 3
Calculate Sample Size
Get the required sample size per group.
Examples
Medium Effect Size
Problem:
d=0.5, σ=1, α=0.05, power=0.8. Find n.
Solution:
- 1.n ≈ 2 × (1.96 + 0.84)² × 1² / 0.5²
- 2.n ≈ 63 per group
Result:n ≈ 63
At least 63 samples per group are needed to detect a medium effect.
Frequently Asked Questions
What is statistical power?
Power is the probability of correctly rejecting the null hypothesis when the alternative is true (typically 0.80 or 80%).
What alpha level is commonly used?
0.05 (5%) is the standard significance level in most statistical tests.