Salīdzināt metodes

	Bonferroni korekcija	Neatkarīgo paraugu t-tests
Nozare	Statistika	Statistika
Saime	Hypothesis test	Hypothesis test
Izcelsmes gads	1961	1908
Autors	Carlo Emilio Bonferroni; formalized for multiple comparisons by Olive Jean Dunn	Student (W. S. Gosset)
Tips	Family-wise error rate (FWER) correction	Parametric mean comparison
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.	Student (1908). The probable error of a mean. Biometrika, 6(1), 1–25.
Citi nosaukumi	Bonferroni adjustment, Bonferroni method, Bonferroni procedure, FWER correction	student t-test, two-sample t-test, unpaired t-test, bağımsız örneklem t-testi
Saistītās	5	4
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 independent samples t-test is a parametric hypothesis test that compares the means of two independent groups to decide whether they differ significantly. It builds on the t-distribution introduced by Student (W. S. Gosset) in 1908 and assumes the measured values are continuous, approximately normally distributed, and have equal variances.