Salīdzināt metodes

	Kolmogorovs-Smirnova tests	Divu paraugu Kolmogorovas-Smirnova tests
Nozare	Statistika	Statistika
Saime	Hypothesis test	Regression model
Izcelsmes gads	1933	1948
Autors	Andrey Nikolaevich Kolmogorov; Nikolai Vasilyevich Smirnov	N. V. Smirnov
Tips	Nonparametric goodness-of-fit test	Nonparametric two-sample distribution test
Pirmavots	Kolmogorov, A. N. (1933). Sulla determinazione empirica di una legge di distribuzione. Giornale dell'Istituto Italiano degli Attuari, 4, 83–91.	Smirnov, N. V. (1948). Table for Estimating the Goodness of Fit of Empirical Distributions. Annals of Mathematical Statistics, 19(2), 279-281.
Citi nosaukumi	KS test, K-S test, one-sample KS test, Kolmogorov-Smirnov Testi	KS two-sample test, two-sample KS test, İki Örneklem Kolmogorov-Smirnov Testi
Saistītās	2	3
Kopsavilkums	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 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.