False discovery rate calculator
Paste p values from a family of tests and choose the target false discovery rate q.
Ranked tests
| Rank | Input position | p | Critical (i/m)q | Adjusted p | Rejected |
|---|---|---|---|---|---|
| Fill in the fields above — the result is computed on this page. | |||||
How do I use this page?
- Paste every p value from one test family.
- Set the target FDR q, commonly 0.05.
- Read the rejection count, cutoff and adjusted p values.
What this page does not do: The standard BH procedure controls FDR under independence or certain positive dependence structures. Other dependence patterns may require Benjamini–Yekutieli or a domain-specific model.
Further reading
Theory — what is the Benjamini-Hochberg FDR correction?
The Benjamini-Hochberg procedure limits the expected share of false discoveries among rejected hypotheses, rather than controlling the risk of one error across the whole family. The calculator sorts p values ascending, compares each against a threshold of (i/m)q based on rank and test count, then picks the largest rank meeting that condition as the cutoff. Adjusted p values are derived from this same procedure. Unlike Bonferroni, which guards against even one type I error, BH is less conservative with many tests.
Frequently asked questions
How does FDR differ from Bonferroni?
Does input order matter?
See also
A/B test calculator
Compare two proportions in an A/B test. Calculate conversion rates, difference, uplift, z score, p value and c
A/B test planning — sample size, MDE and duration
Plan a two-proportion experiment, estimate detectable effect and traffic duration.
ACF and PACF autocorrelation calculator
Calculate ACF and PACF across time-series lags. Review the chart, reference bounds and coefficient table.