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Updated 2026-03-07 UTC
Multiple Comparisons Correction — Bonferroni, Holm, Benjamini–Hochberg — GetCalcMaster
Multiple comparisons corrections explained: why p-values break with many tests, and how to apply Bonferroni, Holm–Bonferroni, and Benjamini–Hochberg (FDR).
If you test many hypotheses, “p < 0.05” stops meaning what you think it means. Multiple-comparisons corrections control error rates when you run many tests (A/B variants, many metrics, many genes, many features).
Important: Educational. Always pre-register or clearly separate confirmatory vs exploratory analyses when possible.
What this calculator is
The Statistics Calculator is an interactive tool inside GetCalcMaster. It’s designed to help you explore scenarios, understand formulas, and document assumptions.
Key features
- Explains FWER vs FDR in plain terms
- Shows how to adjust α or adjust p-values
- Includes common methods: Bonferroni, Holm, Benjamini–Hochberg
- Highlights practical tradeoffs: strictness vs power
Formula
Bonferroni: α' = α / m; adjusted p = min(1, p*m)
Holm (step-down): compare sorted p(i) to α/(m-i+1)
Benjamini–Hochberg (FDR): find largest i where p(i) ≤ (i/m)·qQuick examples
If you test m=20 hypotheses at α=0.05, Bonferroni uses α'=0.0025 per test.BH/FDR often keeps more findings than Bonferroni, especially in exploratory work.
How to use it (quick steps)
- Count the number of comparisons m (tests).
- Choose the error rate you want to control: FWER (strict) or FDR (more power).
- Apply a correction method (Bonferroni/Holm for FWER, BH for FDR).
- Report the method and m alongside your results.
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FAQ
Is this calculator official?
No. GetCalcMaster provides educational estimates and learning tools. Always verify against official definitions, documents, or professional advice.
Do you store my inputs on the server?
No. Calculations run locally in your browser. Optional remember/restore features (if enabled) use local browser storage.
Tip: For reproducible work, save your inputs and reasoning in Notebook.