Comparer des méthodes

	Test de Lilliefors pour la normalité	Test de Kolmogorov-Smirnov à deux échantillons
Domaine	Statistique	Statistique
Famille	Regression model	Regression model
Année d'origine	1967	1948
Auteur d'origine	Hubert W. Lilliefors	N. V. Smirnov
Type	Goodness-of-fit / normality test	Nonparametric two-sample distribution test
Source fondatrice	Lilliefors, H. W. (1967). On the Kolmogorov-Smirnov Test for Normality with Mean and Variance Unknown. Journal of the American Statistical Association, 62(318), 399-402.	Smirnov, N. V. (1948). Table for Estimating the Goodness of Fit of Empirical Distributions. Annals of Mathematical Statistics, 19(2), 279-281.
Alias	Lilliefors corrected Kolmogorov-Smirnov test, Lilliefors normality test, Lilliefors Testi	KS two-sample test, two-sample KS test, İki Örneklem Kolmogorov-Smirnov Testi
Apparentées	5	3
Résumé	The Lilliefors test is a goodness-of-fit test that checks whether a continuous sample comes from a normal (or exponential) distribution when the mean and variance are unknown and estimated from the data. Introduced by Hubert W. Lilliefors in 1967, it adjusts the critical values of the Kolmogorov-Smirnov test so that they remain valid once the distribution's parameters are estimated rather than known in advance.	The two-sample Kolmogorov-Smirnov test is a nonparametric procedure that asks whether two independent groups are drawn from the same continuous distribution. Building on Smirnov's 1948 tables, it compares the empirical cumulative distribution functions (CDFs) of the two samples and uses their maximum absolute distance as the test statistic.