Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Correlación de rangos Tau de Kendall× | Análisis del tamaño del efecto× | |
|---|---|---|
| Campo | Estadística | Estadística |
| Familia | Hypothesis test | Hypothesis test |
| Año de origen≠ | 1938 | 1969 (first edition); 1988 (definitive second edition) |
| Autor original≠ | Maurice G. Kendall | Jacob Cohen |
| Tipo≠ | Nonparametric rank correlation | Standardized magnitude estimation |
| Fuente seminal≠ | Kendall, M. G. (1938). A new measure of rank correlation. Biometrika, 30(1/2), 81–93. DOI ↗ | Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805802832 |
| Alias | Kendall tau, Kendall rank correlation, tau-b, tau-c | effect magnitude estimation, standardized effect measure, practical significance analysis, ES analysis |
| Relacionados | 4 | 4 |
| Resumen≠ | Kendall's tau is a nonparametric measure of the ordinal association between two variables. It quantifies how consistently the relative ordering of one variable matches the ordering of another across all observation pairs, making it robust to outliers and suitable for ordinal or non-normally distributed data. | Effect size analysis quantifies the practical magnitude of a statistical result independently of sample size. Rather than asking only whether a difference or relationship is statistically significant, it asks how large it is, using standardized indices such as Cohen's d, eta-squared, omega-squared, or Pearson's r that allow direct comparison across studies and populations. |
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