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Détecteur Valeurs Aberrantes
Trouve les valeurs aberrantes via les clôtures IQR, le z-score et le z-score modifié basé sur MAD à la fois et explique désaccord. Avertit quand petit échantillon rend test z-score mathématiquement incapable. Permet choisir convention quartile.
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Distribution
Median
Mean
Std deviation
IQR
| Method | Range considered normal | Flagged | Values |
|---|
Every value, scored
| Value | z | modified z | Flagged by |
|---|
Calculated in this page; nothing is uploaded. An outlier is a value that does not fit a model, which is not the same as a value that is wrong — these methods tell you where to look, not what to delete.
How Détecteur Valeurs Aberrantes works
- Open Détecteur Valeurs Aberrantes and review the example state before entering your own values.
- Enter or select the information needed for Détecteur Valeurs Aberrantes.
- Review the result and adjust the inputs if you want to compare another case.
Finds outliers by IQR fences, z-score and the MAD-based modified z-score at once, and explains disagreement. Warns when a small sample makes the z-score test mathematically unable to flag anything, and lets you choose the quartile convention. The interactive workspace runs in your browser, so you can review the result without creating an account.
FAQ
What is Détecteur Valeurs Aberrantes used for?
Finds outliers by IQR fences, z-score and the MAD-based modified z-score at once, and explains disagreement. Warns when a small sample makes the z-score test mathematically unable to flag anything, and lets you choose the quartile convention.
Do I need an account?
No. The tool is available directly in the browser without an account or sign-up.
What should I do if the result looks unexpected?
Check the entered values and compare them with the guidance shown in Détecteur Valeurs Aberrantes. Use the result as a planning aid and verify important decisions independently.