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| Corrélation Robuste (Spearman, Kendall et Biweight)× | Coefficient de corrélation de rang de Spearman× | |
|---|---|---|
| Domaine | Statistique | Statistique |
| Famille≠ | Regression model | Hypothesis test |
| Année d'origine≠ | 2012 | 1904 |
| Auteur d'origine≠ | Spearman rank, Kendall tau; biweight from Wilcox / Shevlyakov & Oja robust statistics tradition | Charles Spearman |
| Type≠ | Robust correlation measures | Nonparametric rank-based correlation |
| Source fondatrice≠ | Wilcox, R. R. (2012). Introduction to Robust Estimation and Hypothesis Testing. Academic Press. ISBN: 978-0123869838 | Spearman, C. (1904). The proof and measurement of association between two things. The American Journal of Psychology, 15, 72–101. DOI ↗ |
| Alias≠ | Spearman correlation, Kendall tau, biweight midcorrelation, rank correlation | Spearman's rho, Spearman rank-order correlation, Spearman Sıra Korelasyonu |
| Apparentées≠ | 5 | 4 |
| Résumé≠ | Robust Correlation is a family of association measures that resist outliers, covering Spearman's rank correlation, Kendall's tau, and the biweight midcorrelation. Drawing on the robust-statistics tradition described by Wilcox (2012) and Shevlyakov & Oja (2016), it measures how strongly two variables move together without being distorted by a few extreme points. | The Spearman rank correlation coefficient (ρ) is a nonparametric measure of the monotonic association between two variables. Introduced by Charles Spearman in 1904, it converts raw observations to ranks and measures how consistently one variable increases as the other increases, without assuming a normal distribution or a linear relationship. |
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