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Vald-Volfovicov test pojava (Wald-Wolfowitz Runs Test)×Durbin-Watsonov test za autokorelaciju×
OblastStatistikaEkonometrija
PorodicaHypothesis testRegression model
Godina nastanka19401950
TvoracAbraham Wald & Jacob WolfowitzJames Durbin & Geoffrey Watson
TipNonparametric randomness testTest for first-order residual autocorrelation
Temeljni izvorWald, A. & Wolfowitz, J. (1940). On a test whether two samples are from the same population. Annals of Mathematical Statistics, 11(2), 147–162. DOI ↗Durbin, J., & Watson, G. S. (1950). Testing for serial correlation in least squares regression: I. Biometrika, 37(3/4), 409–428. DOI ↗
Drugi naziviWald-Wolfowitz test, runs test for randomness, Runs Testi (Wald-Wolfowitz)DW test, Durbin-Watson statistic, Durbin-Watson otokorelasyon testi
Srodne54
SažetakThe 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.
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ScholarGateUporedite metode: Runs Test · Durbin-Watson Test. Preuzeto 2026-06-18 sa https://scholargate.app/sr/compare