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{{g}}The accursed part of your probability distribution, where you discover it diverges from the [[normal distribution]] lazily factored into all your models. | {{g}} | ||
The accursed part of your [[probability]] distribution, where you discover it diverges from the [[normal distribution]] lazily factored into all your models. | |||
In probability theory, “kurtosis” (from Greek: κυρτός, meaning “curved”) is the measure of the fatness of the tails of a distribution of variables. Higher kurtosis corresponds to greater deviation from the [[mean]] — more [[outlier]]s — and is less interested in the shape of the distribution close to the mean. | In probability theory, “kurtosis” (from Greek: κυρτός, meaning “curved”) is the measure of the fatness of the tails of a distribution of variables. Higher kurtosis corresponds to greater deviation from the [[mean]] — more [[outlier]]s — and is less interested in the shape of the distribution close to the mean. | ||
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===Leptokurtic distributions are from Mars, platykurtic distributions are from Venus=== | ===Leptokurtic distributions are from Mars, platykurtic distributions are from Venus=== | ||
''' | '''“Platykurtic” distributions: Mediocristan''': Distributions with ''lower'' kurtosis than 3 are “platykurtic”, and will produce fewer outliers than a [[normal distribution]]. For example, a [[uniform distribution]] — eg a coin toss, or a deck of cards — which does not produce outliers art all. You can’t get an 11 of hearts. | ||
''' | '''“Leptokurtic” distributions: Extremistan''': Distributions with ''greater'' kurtosis than 3 are “leptokurtic”. The tails of a leptokurtic distribution will be fatter — they will tend to zero more slowly than those of a normal distribution, and there will be more outliers. | ||
{{Sa}} | |||
*[[Lentil convexity]] | |||