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Formula:
Statistical power (1 - β) is the probability of correctly rejecting a false null hypothesis. Its calculation is complex and depends on several factors:
- Significance Level (Alpha, α): The probability of making a Type I error (false positive).
- Effect Size (d, f, ω, η²): The magnitude of the difference or relationship you expect to find.
- Sample Size (n): The number of observations or participants in your study.
- Type of Statistical Test: The specific test being used (e.g., t-test, ANOVA, chi-square).
For a two-sample independent t-test, the sample size per group (n) is often approximated by:
n ≈ ( (Zα/2 + Zβ)² × 2 ) / d²
where Z values correspond to the standard normal distribution quantiles for the given α and β (1-Power) levels, and 'd' is Cohen's d effect size.