विधियों की तुलना करें

	बेयसियन बूटस्ट्रैप (रूबिन)	फिशर एग्जैक्ट रैंडमाइजेशन इन्फेरेंस
क्षेत्र	सांख्यिकी	सांख्यिकी
परिवार	Regression model	Regression model
उद्भव वर्ष	1981	1935
प्रवर्तक	Rubin (1981); large-sample theory by Lo (1987)	Ronald A. Fisher
प्रकार	Resampling / posterior simulation	Exact permutation-based inference
मौलिक स्रोत	Rubin, D. B. (1981). The Bayesian Bootstrap. The Annals of Statistics, 9(1), 130-134.	Fisher, R. A. (1935). The Design of Experiments. Oliver & Boyd.
उपनाम	Bayesian Bootstrap (Rubin), Rubin bootstrap, Dirichlet-weighted bootstrap	fisher randomization test, permutation inference, exact randomization test, randomizasyon çıkarımı (fisher exact randomization)
संबंधित	5	5
सारांश	The Bayesian Bootstrap, introduced by Donald B. Rubin in 1981, is a resampling method that produces a Bayesian counterpart to the frequentist bootstrap by assigning each observation a random weight drawn from a Dirichlet distribution. It yields a full posterior distribution for a statistic and allows prior information to be incorporated.	Randomization inference, introduced by Ronald A. Fisher in The Design of Experiments (1935), computes an exact p-value by evaluating a test statistic across all possible treatment assignments under Fisher's sharp null hypothesis. It is regarded as the gold standard for analysing designed experiments because its validity rests on the known assignment mechanism rather than on distributional assumptions.