Comparer des méthodes

	Statistiques descriptives robustes	Test t robuste pour échantillons indépendants
Domaine	Statistique	Statistique
Famille	Hypothesis test	Hypothesis test
Année d'origine	1960s–1970s	1974–1990s
Auteur d'origine	John W. Tukey, Peter J. Huber, Frank Hampel	Rand R. Wilcox; Karen K. Yuen (trimmed-mean form)
Type	Resistant summary measures	Robust parametric mean comparison
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	Yuen's t-test, trimmed-mean t-test, Winsorized t-test, robust two-sample test
Apparentées	5	2
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 independent samples t-test compares the central tendency of two independent groups using trimmed means and Winsorized variances, making it substantially less sensitive to outliers and non-normality than the classical Student or Welch t-test. The most widely used form is Yuen's test, which also accommodates unequal variances across groups.