🎉 75% of content is free forever — Unlock Premium from $10/mo →
CW
Search courses…
💼 Servicesℹ️ About✉️ ContactView Pricing Plansfrom $10

Bonferroni Correction — When and How to Apply It

Hypothesis TestingAdvanced Topics🟢 Free Lesson

Advertisement

Bonferroni Correction

Hypothesis Testing

The Simplest Defense Against False Positives

The Bonferroni correction controls the family-wise error rate by dividing α by the number of tests. It is conservative but guarantees rigorous error control in any testing situation.

  • Clinical Trials — Protecting against false positives in multi-endpoint studies
  • Genome-Wide Association Studies — Controlling errors across millions of genetic markers
  • Post-Hoc Analysis — Correcting for multiple comparisons after data exploration

Simplicity and rigor make Bonferroni the gold standard for error control.


The simplest correction for multiple testing: divide α by the number of tests.

Or equivalently: multiply each p-value by m and compare to original α.


Python Implementation


When Bonferroni Is Too Conservative


Key Takeaways

Need Expert Statistics Help?

Get personalized tutoring, project support, or professional consulting.

Advertisement