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This advice is insane. Except in specific settings (where a sensor may be misbehaving, where a survey respondent clearly just picked random choices) outliers are really just outlying values and should be kept in the analysis, or at most clipped / winsorized. When submitting to a scientific journal, admitting that outliers were removed without first inspecting why they are there can be enough for an instant rejection, and rightly so.


Twyman's law doesn't state you should ignore those outliers it just predicts that they are more likely to be mistakes then genuine.


I like using the Olympic style of scoring where they lop off the top and bottom scores to account for the cranky overly lenient judges.




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