Vertaile menetelmiä
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| Bayesiläinen ristiintaulukointianalyysi× | Khii toiseen tunnusluvun riippumattomuustesti× | |
|---|---|---|
| Tieteenala | Tilastotiede | Tilastotiede |
| Menetelmäperhe | Hypothesis test | Hypothesis test |
| Syntyvuosi≠ | 1974 | 1900 |
| Kehittäjä≠ | Gunel & Dickey | Karl Pearson |
| Tyyppi≠ | Bayesian association test | Nonparametric test of association |
| Alkuperäislähde≠ | Gunel, E., & Dickey, J. (1974). Bayes factors for independence in contingency tables. Biometrika, 61(3), 545–557. 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 ↗ |
| Rinnakkaisnimet | Bayesian chi-square test, Bayesian contingency table test, Bayes factor association test, Bayesian crosstab analysis | chi-squared test, Pearson's chi-square test, test of independence, ki-kare bağımsızlık testi |
| Liittyvät≠ | 4 | 2 |
| Tiivistelmä≠ | Bayesian cross-tabulation analysis tests whether two categorical variables are associated by computing a Bayes factor that quantifies the evidence for an association model against an independence model. Unlike classical chi-square testing, it provides a continuous measure of evidence, supports the null hypothesis directly, and updates naturally with prior knowledge about the cell probabilities. | 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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