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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.
Trinn-for-trinn guide
- 1Sort data ascending
- 2Remove bottom k% and top k% of observations
- 3Calculate arithmetic mean of remaining values
Løste eksempler
Inndata
Data: 2,4,5,6,7,100 · 10% trim
Resultat
Trimmed mean 5.5 vs raw mean 20.7
Outlier 100 inflates raw mean dramatically
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