قارن الطرق
راجع الطرق التي اخترتها جنبًا إلى جنب؛ الصفوف المختلفة مميَّزة.
| تحليل الجداول المتقاطعة البايزي× | اختبار مربع كاي للاستقلال× | |
|---|---|---|
| المجال | الإحصاء | الإحصاء |
| العائلة | Hypothesis test | Hypothesis test |
| سنة النشأة≠ | 1974 | 1900 |
| صاحب الطريقة≠ | Gunel & Dickey | Karl Pearson |
| النوع≠ | Bayesian association test | Nonparametric test of association |
| المصدر التأسيسي≠ | 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 ↗ |
| الأسماء البديلة | 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 |
| ذات صلة≠ | 4 | 2 |
| الملخص≠ | 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. |
| ScholarGateمجموعة البيانات ↗ |
|
|