False Discovery Rate Calculator

| Added in Statistics

What is False Discovery Rate and Why Should You Care?

The False Discovery Rate (FDR) measures the percentage of false positives among your significant findings. In research with multiple tests, understanding FDR helps ensure your conclusions are trustworthy and not just statistical flukes.

The Formula

[\text{FDR} = \frac{\text{Number of False Discoveries}}{\text{Number of Tests Performed}} \times 100]

Where:

  • Number of False Discoveries is the count of tests that mistakenly indicated a positive result
  • Number of Tests Performed is the total count of tests conducted

Calculation Example

Suppose you performed 800 tests and found 32 were false discoveries:

[\text{FDR} = \frac{32}{800} \times 100 = 4%]

The False Discovery Rate is 4%, meaning 4% of your positive findings may be false.

Quick Reference

Variables Value
False Discoveries 32
Tests Performed 800
FDR 4%

Why FDR Matters

This is especially relevant in fields like genomics or biomedical research where large-scale testing is common. By managing your FDR, you ensure that your conclusions are more trustworthy and lead to real, actionable insights.

Frequently Asked Questions

False discovery rate is the expected proportion of false positives among all positive results in multiple hypothesis testing.

FDR equals the number of false discoveries divided by total tests performed, multiplied by 100 for a percentage.

Managing FDR ensures research findings are reliable and not just statistical flukes, which is crucial for scientific integrity.

Commonly, an FDR of 5% or less is considered acceptable, meaning at most 5% of significant findings are expected to be false positives.