Winsorizing or winsorization is the transformation of statistics by limiting extreme values in the statistical data to reduce the effect of possibly spurious outliers.
The distribution of many statistics can be heavily influenced by outliers, values that are 'way outside' the bulk of the data.
Winsorized estimators are usually more robust to outliers than their more standard forms, although there are alternatives, such as trimming (see below), that will achieve a similar effect.
Accordingly, a 90% winsorization would result in the following data set: After winsorization the mean has dropped to nearly half its previous value, and is consequently more in line or congruent with the data set from which it is calculated.
In a trimmed estimator, the extreme values are discarded; in a winsorized estimator, the extreme values are instead replaced by certain percentiles (the trimmed minimum and maximum).