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Beijiešu Vilkoksona zīmju rangu tests×Paired paraugu t-tests×
NozareStatistikaStatistika
SaimeHypothesis testHypothesis test
Izcelsmes gads2014–20171908
AutorsBenavoli, Corani, Mangili, and colleaguesStudent (W. S. Gosset)
TipsBayesian nonparametric paired testParametric mean comparison
PirmavotsBenavoli, A., Corani, G., & Mangili, F. (2014). Should we really use post-hoc tests based on mean-ranks? Journal of Machine Learning Research, 17(5), 1–10. link ↗Student (1908). The probable error of a mean. Biometrika, 6(1), 1–25. DOI ↗
Citi nosaukumiBayesian signed-rank test, Bayesian nonparametric paired comparison, Benavoli signed-rank Bayesian test, signed-rank Bayesian hypothesis testdependent t-test, matched pairs t-test, repeated measures t-test, within-subjects t-test
Saistītās23
KopsavilkumsThe Bayesian Wilcoxon signed-rank test is a Bayesian nonparametric method for comparing two paired or related samples. Rather than returning a single p-value, it produces posterior probabilities that one condition is better, practically equivalent, or worse than the other, enabling richer and more interpretable inference for paired continuous or ordinal data without assuming normality.The paired samples t-test is a parametric hypothesis test that compares the means of two related measurements from the same subjects or matched pairs to determine whether the average difference is significantly different from zero. It leverages the dependency between observations to produce a more powerful test than its independent-samples counterpart.
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ScholarGateSalīdzināt metodes: Bayesian Wilcoxon signed-rank test · Paired samples t-test. Izgūts 2026-06-19 no https://scholargate.app/lv/compare