Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Байєсівський тест знакозмінних рангів Вілкоксона× | Парний t-критерій Стьюдента× | |
|---|---|---|
| Галузь | Статистика | Статистика |
| Родина | Hypothesis test | Hypothesis test |
| Рік появи≠ | 2014–2017 | 1908 |
| Автор методу≠ | Benavoli, Corani, Mangili, and colleagues | Student (W. S. Gosset) |
| Тип≠ | Bayesian nonparametric paired test | Parametric mean comparison |
| Основоположне джерело≠ | 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 ↗ |
| Інші назви | 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 |
| Пов'язані≠ | 2 | 3 |
| Підсумок≠ | 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. |
| ScholarGateНабір даних ↗ |
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