Salīdzināt metodes

	Permutācijas (randomizācijas) tests	Džeknaifa atkārtotā izlases metode
Nozare	Statistika	Statistika
Saime	Regression model	Regression model
Izcelsmes gads	2005	1956
Autors	Good (2005); Edgington & Onghena (2007); resampling tradition	Quenouille (1956); reviewed by Miller (1974)
Tips	Nonparametric resampling test	Resampling / bias and variance estimation
Pirmavots	Good, P. (2005). Permutation, Parametric and Bootstrap Tests of Hypotheses (3rd ed.). Springer. ISBN: 978-0387202792	Quenouille, M. H. (1956). Notes on Bias in Estimation. Biometrika, 43(3/4), 353-360.
Citi nosaukumi	randomization test, exact permutation test, re-randomization test, Permütasyon Testi	leave-one-out resampling, Quenouille-Tukey jackknife, delete-one jackknife, Jackknife Yeniden Örnekleme
Saistītās	5	5
Kopsavilkums	The permutation test is a nonparametric resampling procedure that builds the sampling distribution of a test statistic directly from the data by repeatedly shuffling the group labels. Developed in the resampling tradition and treated systematically by Good (2005) and Edgington & Onghena (2007), it requires no parametric distributional assumption and yields an exact p-value.	The jackknife is a classical resampling method that estimates the bias and variance of a statistic by systematically recomputing it with one observation left out at a time. Introduced by Quenouille in 1956 and later reviewed by Miller in 1974, it predates the bootstrap and remains a simple, deterministic tool for assessing estimator stability.