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| Statistiques descriptives robustes× | Corrélation de Pearson Robuste× | |
|---|---|---|
| Domaine | Statistique | Statistique |
| Famille | Hypothesis test | Hypothesis test |
| Année d'origine≠ | 1960s–1970s | 1970s–1990s |
| Auteur d'origine≠ | John W. Tukey, Peter J. Huber, Frank Hampel | Rand R. Wilcox and predecessors in robust statistics |
| Type≠ | Resistant summary measures | Robust bivariate association measure |
| Source fondatrice≠ | Tukey, J. W. (1977). Exploratory Data Analysis. Addison-Wesley. ISBN: 978-0201076165 | Wilcox, R. R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Academic Press. ISBN: 978-0123869838 |
| Alias | resistant statistics, outlier-resistant summary statistics, robust summary measures, robust location and scale estimation | winsorized correlation, percentage bend correlation, robust r, outlier-resistant correlation |
| Apparentées≠ | 5 | 3 |
| Résumé≠ | Robust descriptive statistics summarize the location, spread, and shape of a dataset using measures that remain meaningful even when a fraction of the data contains outliers or severe departures from normality. Core tools include the median, trimmed mean, interquartile range (IQR), and median absolute deviation (MAD), all of which are resistant to contamination that would distort the classic mean and standard deviation. | The robust Pearson correlation is an outlier-resistant measure of linear association between two continuous variables. By applying Winsorizing, trimming, or percentage-bend transformations before computing the classic Pearson r, it retains the interpretability of a correlation coefficient while dramatically reducing the distortion caused by extreme values. |
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