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| 베이즈 교차표 분석× | 교차표 분석× | |
|---|---|---|
| 분야 | 통계학 | 통계학 |
| 계열 | Hypothesis test | Hypothesis test |
| 기원 연도≠ | 1974 | 1900 |
| 창시자≠ | Gunel & Dickey | Karl Pearson |
| 유형≠ | Bayesian association test | Descriptive and inferential categorical analysis |
| 원전≠ | 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 ↗ |
| 별칭 | Bayesian chi-square test, Bayesian contingency table test, Bayes factor association test, Bayesian crosstab analysis | crosstab, contingency table analysis, two-way frequency table, bivariate frequency analysis |
| 관련≠ | 4 | 5 |
| 요약≠ | 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. | Cross-tabulation analysis (contingency table analysis) is a foundational descriptive and inferential technique for examining the relationship between two or more categorical variables. It arranges observed frequencies into a table of rows and columns, enabling visual inspection of patterns and formal chi-square testing of independence between the variables. |
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