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| Bayesowski test chi-kwadrat× | Test niezależności chi-kwadrat× | |
|---|---|---|
| Dziedzina | Statystyka | Statystyka |
| Rodzina | Hypothesis test | Hypothesis test |
| Rok powstania≠ | 1967 | 1900 |
| Twórca≠ | I. J. Good; extended by Gunel, Dickey, and Wagenmakers et al. | Karl Pearson |
| Typ≠ | Bayesian nonparametric association test | Nonparametric test of association |
| Źródło pierwotne≠ | Good, 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 ↗ |
| Inne nazwy | Bayesian contingency table test, Bayes factor chi-square, Bayesian goodness-of-fit test, Bayesian association test | chi-squared test, Pearson's chi-square test, test of independence, ki-kare bağımsızlık testi |
| Pokrewne≠ | 3 | 2 |
| Podsumowanie≠ | The 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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