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| Μπεϋζιανό Τεστ Wilcoxon Προσημασμένης Κατάταξης× | Έλεγχος t δειγμάτων ζευγών× | |
|---|---|---|
| Πεδίο | Στατιστική | Στατιστική |
| Οικογένεια | Hypothesis test | Hypothesis test |
| Έτος προέλευσης≠ | 2014–2017 | 1908 |
| Δημιουργός≠ | Benavoli, Corani, Mangili, and colleagues | Student (W. S. Gosset) |
| Τύπος≠ | Bayesian nonparametric paired test | Parametric mean comparison |
| Θεμελιώδης πηγή≠ | 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. link ↗ | Student (1908). The probable error of a mean. Biometrika, 6(1), 1–25. DOI ↗ |
| Εναλλακτικές ονομασίες | Bayesian signed-rank test, Bayesian nonparametric paired comparison, Benavoli signed-rank Bayesian test, signed-rank Bayesian hypothesis test | dependent t-test, matched pairs t-test, repeated measures t-test, within-subjects t-test |
| Συναφείς≠ | 2 | 3 |
| Σύνοψη≠ | 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 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. |
| ScholarGateΣύνολο δεδομένων ↗ |
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