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While skewness is the measure of symmetry, or if one would like to be more precise, the lack of symmetry, kurtosis is a measure of data that is either peaked or flat relative to a normal distribution of a data set.
* Skewness:
A distribution is symmetric if both the left and right sides are the same relative to the center point.
* Kurtosis: A data set that tends to have a distant peak near the mean value, have heavy tails, or decline rapidly is a measure of high kurtosis.
Data sets with low Kurtosis would obviously be opposite with a flat mean at the top, and a distribution that is uniform.
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∙ 15y ago
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In probability theory and statistics, kurtosis (from the Greek word κυρτός, kyrtos or kurtos, meaning bulging) is a measure of the "peakedness" of the probability distribution of a real-valued random variable. Higher kurtosis means more of the variance is due to infrequent extreme deviations, as opposed to frequent modestly sized deviations. Sometimes kurtosis gets confused with skewness, so I have added links to both these terms.
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