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Bayesiaanse Chi-kwadraattoets×Chi-kwadraattoets voor Onafhankelijkheid×
VakgebiedStatistiekStatistiek
FamilieHypothesis testHypothesis test
Jaar van ontstaan19671900
GrondleggerI. J. Good; extended by Gunel, Dickey, and Wagenmakers et al.Karl Pearson
TypeBayesian nonparametric association testNonparametric test of association
Oorspronkelijke bronGood, I. J. (1967). A Bayesian significance test for multinomial distributions. Journal of the Royal Statistical Society: Series B (Methodological), 29(3), 399–418. DOI ↗Pearson, K. (1900). On the criterion that a given system of deviations from the probable in the case of a correlated system of variables is such that it can be reasonably supposed to have arisen from random sampling. Philosophical Magazine, 50(302), 157–175. DOI ↗
AliassenBayesian contingency table test, Bayes factor chi-square, Bayesian goodness-of-fit test, Bayesian association testchi-squared test, Pearson's chi-square test, test of independence, ki-kare bağımsızlık testi
Verwant32
SamenvattingThe Bayesian chi-square test evaluates independence or goodness-of-fit in frequency tables using Bayes factors rather than classical p-values. It quantifies evidence for or against an association between categorical variables, updating prior beliefs with observed counts and delivering an odds-like ratio that distinguishes 'no evidence' from 'evidence of no effect'.The chi-square test of independence is a nonparametric hypothesis test that examines whether two categorical variables are associated by comparing observed and expected frequencies in a cross-tabulation. It rests on the chi-square criterion introduced by Karl Pearson in 1900.
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ScholarGateMethoden vergelijken: Bayesian chi-square test · Chi-square test. Geraadpleegd op 2026-06-17 via https://scholargate.app/nl/compare