Methoden vergelijken

	Kolmogorov-Smirnov Test	Lilliefors-test voor normaliteit
Vakgebied	Statistiek	Statistiek
Familie	Hypothesis test	Regression model
Jaar van ontstaan	1933	1967
Grondlegger	Andrey Nikolaevich Kolmogorov; Nikolai Vasilyevich Smirnov	Hubert W. Lilliefors
Type	Nonparametric goodness-of-fit test	Goodness-of-fit / normality test
Oorspronkelijke bron	Kolmogorov, A. N. (1933). Sulla determinazione empirica di una legge di distribuzione. Giornale dell'Istituto Italiano degli Attuari, 4, 83–91.	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.
Aliassen	KS test, K-S test, one-sample KS test, Kolmogorov-Smirnov Testi	Lilliefors corrected Kolmogorov-Smirnov test, Lilliefors normality test, Lilliefors Testi
Verwant	2	5
Samenvatting	The Kolmogorov-Smirnov (KS) test is a nonparametric goodness-of-fit test that assesses whether a sample comes from a specified theoretical distribution, such as the normal or exponential. First formalised by Andrey Kolmogorov in 1933 and further developed by Nikolai Smirnov in 1948, it compares the empirical cumulative distribution function of the observed data against a target theoretical CDF and quantifies their maximum absolute deviation.	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.