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Because wages are non-Gaussian, standard deviation doesn't mean anything in this context.



Interesting. Most income graphs I've seen appear to be normally distributed -- could you explain what would cause them not to be, or provide any examples that demonstrate non-Gaussian distributions?

But if wages are non-Gaussian, how would trimming the top and bottom 5% off of your sample be any better than using standard deviation ranges to control for outliers? The assumption that outliers are to be found on the top and bottom of your range is one that seems to apply to Gaussian distributions, and doesn't necessarily hold for others, regardless of whether you are using fixed percentage values or standard deviation thresholds. For example, in a bimodal distribution, outliers might be found in the center.




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