Assertion: distribution's kurtosis | /r/HasProperty | bounded by the square of the skewness
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Source sentences:
text: This minimum value is reached when all the probability density is entirely concentrated at each end x = 0 and x = 1, with nothing in between: a 2-point Bernoulli distribution with equal probability 1/2 at each end (a coin toss: see section below "Kurtosis bounded by the square of the skewness" for further discussion).
text: From this last expression, one can obtain the same limits published practically a century ago by Karl Pearson in his paper, for the beta distribution (see section below titled "Kurtosis bounded by the square of the skewness").
text: Kurtosis bounded by the square of the skewness [ edit ]