Comparer des méthodes

	Test de normalité d'Anderson-Darling	Test de Lilliefors pour la normalité
Domaine	Statistique	Statistique
Famille	Regression model	Regression model
Année d'origine	1952	1967
Auteur d'origine	Anderson & Darling (1952); EDF tables by Stephens (1974)	Hubert W. Lilliefors
Type	Empirical distribution function (EDF) goodness-of-fit test	Goodness-of-fit / normality test
Source fondatrice	Anderson, T. W., & Darling, D. A. (1952). Asymptotic Theory of Certain 'Goodness of Fit' Criteria Based on Stochastic Processes. The Annals of Mathematical Statistics, 23(2), 193-212.	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.
Alias	Anderson-Darling Normallik Testi, A-squared test, AD test, Anderson-Darling goodness-of-fit test	Lilliefors corrected Kolmogorov-Smirnov test, Lilliefors normality test, Lilliefors Testi
Apparentées	5	5
Résumé	The Anderson-Darling test is an empirical distribution function (EDF) goodness-of-fit test, introduced by Anderson and Darling in 1952, that checks whether a continuous sample comes from a specified distribution such as the normal, exponential, or Weibull. By weighting deviations more heavily in the tails, it detects departures in the distribution's extremes more powerfully than the Kolmogorov-Smirnov test.	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.