Linganisha mbinu

	Kipimo cha Bayesian Mann-Whitney U	Kipimo cha Bayesian Wilcoxon Signed-Rank
Nyanja	Takwimu	Takwimu
Familia	Hypothesis test	Hypothesis test
Mwaka wa asili	2020 (Bayesian formulation); 1947 (classical test)	2014–2017
Mwanzilishi	van Doorn, Ly, Marsman, Wagenmakers (building on Mann & Whitney 1947)	Benavoli, Corani, Mangili, and colleagues
Aina	Bayesian nonparametric two-sample test	Bayesian nonparametric paired test
Chanzo asilia	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.	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.
Majina mbadala	Bayesian rank-sum test, Bayesian Wilcoxon rank-sum test, Bayesian nonparametric two-sample test	Bayesian signed-rank test, Bayesian nonparametric paired comparison, Benavoli signed-rank Bayesian test, signed-rank Bayesian hypothesis test
Zinazohusiana	3	2
Muhtasari	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.	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.