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Robuster Chi-Quadrat-Test×Fishers Exakter Test×
FachgebietStatistikStatistik
FamilieHypothesis testHypothesis test
Entstehungsjahr1984 (power divergence); 1900 (Pearson baseline)1922
UrheberCressie & Read (power divergence framework); Pearson chi-square extended by multiple authorsR. A. Fisher
TypRobust categorical association / goodness-of-fit testExact test of independence for categorical data
Wegweisende QuelleCressie, N., & Read, T. R. C. (1984). Multinomial goodness-of-fit tests. Journal of the Royal Statistical Society: Series B, 46(3), 440–464. DOI ↗Fisher, R. A. (1922). On the interpretation of chi-squared from contingency tables, and the calculation of P. Journal of the Royal Statistical Society, 85(1), 87–94. DOI ↗
Aliasnamenrobust chi-squared test, Cressie-Read power divergence test, adjusted chi-square test, robust contingency testFisher-Irwin test, exact test of independence, Fisher'ın Kesin Testi
Verwandt32
ZusammenfassungThe robust chi-square test extends the classic Pearson chi-square framework to remain reliable when standard assumptions — especially the minimum expected-cell-count rule — are violated. Using power divergence statistics (Cressie & Read, 1984) or resampling-based corrections, it produces valid inferences for sparse contingency tables, small samples, and unbalanced categorical data where the ordinary chi-square approximation breaks down.Fisher's exact test is a nonparametric exact-probability test of independence for small-sample contingency tables, introduced by R. A. Fisher in 1922. Rather than relying on a large-sample approximation, it computes the exact probability of the observed table directly from the hypergeometric distribution.
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ScholarGateMethoden vergleichen: Robust chi-square test · Fisher's exact test. Abgerufen am 2026-06-17 von https://scholargate.app/de/compare