Sammenlign metoder

	Wald-Wolfowitz Runs Test	Kolmogorov-Smirnov Test
Fagområde	Statistik	Statistik
Familie	Hypothesis test	Hypothesis test
Oprindelsesår	1940	1933
Ophavsperson	Abraham Wald & Jacob Wolfowitz	Andrey Nikolaevich Kolmogorov; Nikolai Vasilyevich Smirnov
Type	Nonparametric randomness test	Nonparametric goodness-of-fit test
Oprindelig kilde	Wald, A. & Wolfowitz, J. (1940). On a test whether two samples are from the same population. Annals of Mathematical Statistics, 11(2), 147–162.	Kolmogorov, A. N. (1933). Sulla determinazione empirica di una legge di distribuzione. Giornale dell'Istituto Italiano degli Attuari, 4, 83–91.
Aliasser	Wald-Wolfowitz test, runs test for randomness, Runs Testi (Wald-Wolfowitz)	KS test, K-S test, one-sample KS test, Kolmogorov-Smirnov Testi
Relaterede	5	2
Resumé	The Wald-Wolfowitz runs test is a nonparametric hypothesis test that determines whether a sequence of observations — coded as a series of binary symbols — follows a random pattern or contains systematic structure. Introduced by Abraham Wald and Jacob Wolfowitz in 1940, the test counts the number of uninterrupted runs of identical symbols and asks whether that count is consistent with random arrangement.	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.