Comparer des méthodes

	Analyse de fréquence robuste	Statistiques descriptives robustes
Domaine	Statistique	Statistique
Famille	Hypothesis test	Hypothesis test
Année d'origine	1970s–1980s (foundations); applied to frequency analysis throughout the 1990s–2000s	1960s–1970s
Auteur d'origine	Huber, Hampel, Wilcox and the robust statistics tradition	John W. Tukey, Peter J. Huber, Frank Hampel
Type	Robust descriptive and inferential procedure	Resistant summary measures
Source fondatrice	Wilcox, R. R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Academic Press. ISBN: 978-0123869838	Tukey, J. W. (1977). Exploratory Data Analysis. Addison-Wesley. ISBN: 978-0201076165
Alias	robust count analysis, outlier-resistant frequency analysis, robust distributional analysis	resistant statistics, outlier-resistant summary statistics, robust summary measures, robust location and scale estimation
Apparentées	3	5
Résumé	Robust frequency analysis applies outlier-resistant estimation and resampling or exact methods to the counting and tabulation of categorical data, reducing the distortion caused by extreme observations, sparse cells, or violations of large-sample assumptions that can make conventional frequency summaries misleading.	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.