On Mon, Oct 21, 2013 at 4:29 PM, Tom Lane <tgl@sss.pgh.pa.us> wrote:
Andrew Dunstan <andrew@dunslane.net> writes: > This is why I suggested the standard deviation, and why I find it would > be more useful than just min and max. A couple of outliers will set the > min and max to possibly extreme values but hardly perturb the standard > deviation over a large number of observations.
Hm. It's been a long time since college statistics, but doesn't the entire concept of standard deviation depend on the assumption that the underlying distribution is more-or-less normal (Gaussian)?
It is easy to misinterpret the standard deviation if the distribution is not gaussian, but that is also true of the average. The standard deviation (or the variance) is commonly used with non-gaussian distributions, either because it is the most efficient estimator for those particular distributions, or just because it is so commonly available.