Comparer des méthodes

	Test de Lilliefors pour la normalité	Test de normalité d'Anderson-Darling
Domaine	Statistique	Statistique
Famille	Regression model	Regression model
Année d'origine	1967	1952
Auteur d'origine	Hubert W. Lilliefors	Anderson & Darling (1952); EDF tables by Stephens (1974)
Type	Goodness-of-fit / normality test	Empirical distribution function (EDF) goodness-of-fit 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.	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.
Alias	Lilliefors corrected Kolmogorov-Smirnov test, Lilliefors normality test, Lilliefors Testi	Anderson-Darling Normallik Testi, A-squared test, AD test, Anderson-Darling goodness-of-fit test
Apparentées	5	5
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 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.