Comparer des méthodes

	Test des séries de Wald-Wolfowitz	Test de Durbin-Watson pour l'autocorrélation
Domaine	Statistique	Économétrie
Famille	Hypothesis test	Regression model
Année d'origine	1940	1950
Auteur d'origine	Abraham Wald & Jacob Wolfowitz	James Durbin & Geoffrey Watson
Type	Nonparametric randomness test	Test for first-order residual autocorrelation
Source fondatrice	Wald, A. & Wolfowitz, J. (1940). On a test whether two samples are from the same population. Annals of Mathematical Statistics, 11(2), 147–162.	Durbin, J., & Watson, G. S. (1950). Testing for serial correlation in least squares regression: I. Biometrika, 37(3/4), 409–428.
Alias	Wald-Wolfowitz test, runs test for randomness, Runs Testi (Wald-Wolfowitz)	DW test, Durbin-Watson statistic, Durbin-Watson otokorelasyon testi
Apparentées	5	4
Résumé	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 Durbin-Watson test, developed by James Durbin and Geoffrey Watson in 1950–1951, detects first-order serial correlation in the residuals of a linear regression. Its statistic ranges from 0 to 4, with a value near 2 indicating no autocorrelation, values toward 0 indicating positive autocorrelation, and values toward 4 indicating negative autocorrelation. It remains one of the most reported regression diagnostics despite well-known limitations.