90% winsorized mean sets the bottom 5% to the 5th percentile, the top 5% to the 95th percentile, and then averages the data. In the previous example the trimmed mean would be obtained from the smaller set: {92, 19, 101, 58, 91, 26, 78, 10, 13, 101, 86, 85, 15, 89, 89, 28, −5, 41} (N = 18, mean = 56.5) In this case, the winsorized mean can equivalently be expressed as a weighted average of the truncated mean and the 5th and 95th percentiles (for the 10% winsorized mean, 0.05 times the 5th percentile, 0.9 times the 10% trimmed mean, and 0.05 times the 95th percentile) though in general winsorized statistics need not be expressible in terms of the corresponding trimmed statistic. More formally, they are distinct because the order statistics are not independent. Uses Winsorization is a used in the survey methodology context in order to "trim" extreme survey non-response weights. It is also used in the construction of some stock indexes when looking at the range of certain factors (for example growth and value) for particular stocks. See also Trimmed estimator Huber loss Robust regression References External links Statistical data transformation Robust statistics Articles with example Python (programming language) code Articles with example R code