On 13.03.17 22:38, Antoine Pitrou wrote:
The mean approximates the expected performance over multiple runs (note "expected" is a rigorously defined term in statistics here: see https://en.wikipedia.org/wiki/Expected_value). The median doesn't tell you anything about the expected value (*). So the mean is more informative for the task at hand.
The median tells you that results of a half of runs will be less than the median and results of other half will be larger. This is pretty informative and even more informative than the mean for some applications.
Additionally, while mean and std dev are generally quite well understood, the properties of the median absolute deviation are generally little known.
Std dev is well understood for the distribution close to normal. But when the distribution is too skewed or multimodal (as in your quick example) common assumptions (that 2/3 of samples are in the range of the std dev, 95% of samples are in the range of two std devs, 99% of samples are in the range of three std devs) are no longer valid.
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