Linganisha mbinu

	Kipimo cha Bayesian Wilcoxon Signed-Rank	Kipimo cha Bayesian Mann-Whitney U
Nyanja	Takwimu	Takwimu
Familia	Hypothesis test	Hypothesis test
Mwaka wa asili	2014–2017	2020 (Bayesian formulation); 1947 (classical test)
Mwanzilishi	Benavoli, Corani, Mangili, and colleagues	van Doorn, Ly, Marsman, Wagenmakers (building on Mann & Whitney 1947)
Aina	Bayesian nonparametric paired test	Bayesian nonparametric two-sample test
Chanzo asilia	Benavoli, 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.	van Doorn, J., Ly, A., Marsman, M., & Wagenmakers, E.-J. (2020). Bayesian rank-based hypothesis testing for the rank sum test, the signed rank test, and Spearman's rho. Journal of Applied Statistics, 47(16), 2984–3006.
Majina mbadala	Bayesian signed-rank test, Bayesian nonparametric paired comparison, Benavoli signed-rank Bayesian test, signed-rank Bayesian hypothesis test	Bayesian rank-sum test, Bayesian Wilcoxon rank-sum test, Bayesian nonparametric two-sample test
Zinazohusiana	2	3
Muhtasari	The 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 Bayesian Mann-Whitney U test is a nonparametric Bayesian procedure for comparing two independent groups when data are ordinal or non-normal continuous. Instead of a binary reject/fail-to-reject decision, it quantifies the relative evidence for the null and alternative hypotheses through a Bayes factor, allowing researchers to conclude in favour of either hypothesis or express uncertainty.