Salīdzināt metodes

	Bonferroni korekcija	Procedūra Benjamini-Hochberg (FDR kontrole)
Nozare	Statistika	Statistika
Saime	Hypothesis test	Hypothesis test
Izcelsmes gads	1961	1995
Autors	Carlo Emilio Bonferroni; formalized for multiple comparisons by Olive Jean Dunn	Yoav Benjamini & Yosef Hochberg
Tips	Family-wise error rate (FWER) correction	False discovery rate (FDR) procedure
Pirmavots	Bonferroni, C. E. (1936). Teoria statistica delle classi e calcolo delle probabilità. Pubblicazioni del R Istituto Superiore di Scienze Economiche e Commerciali di Firenze, 8, 3–62.	Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society: Series B, 57(1), 289–300.
Citi nosaukumi	Bonferroni adjustment, Bonferroni method, Bonferroni procedure, FWER correction	BH procedure, FDR control, false discovery rate procedure, Benjamini-Hochberg düzeltmesi
Saistītās	5	3
Kopsavilkums	The Bonferroni correction is a conservative, universally applicable method for controlling the family-wise error rate (FWER) when conducting multiple simultaneous hypothesis tests. Grounded in Bonferroni's 1936 probability inequality and formalized for multiple comparisons by Olive Jean Dunn in 1961, the procedure divides the target significance level α by the number of tests m, ensuring that the probability of making even one false rejection across the entire family of tests does not exceed α.	The Benjamini-Hochberg (BH) procedure, introduced by Yoav Benjamini and Yosef Hochberg in 1995, controls the false discovery rate (FDR) — the expected proportion of false positives among all rejected hypotheses — rather than the probability of any false positive. By tolerating a controlled fraction of false discoveries, it delivers far greater power than family-wise error rate methods such as Bonferroni or Holm, which is why it has become the standard tool for large-scale simultaneous testing in genomics, neuroimaging, and other high-throughput fields.