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A trimmed mean removes a percentage of the most extreme values from each tail before computing the mean, making it robust to outliers while retaining more information than the median.

Guía paso a paso

  1. 1Sort data ascending
  2. 2Remove bottom k% and top k% of observations
  3. 3Calculate arithmetic mean of remaining values

Ejemplos resueltos

Entrada
Data: 2,4,5,6,7,100 · 10% trim
Resultado
Trimmed mean 5.5 vs raw mean 20.7
Outlier 100 inflates raw mean dramatically

Configuración

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