Excess Kurtosis of Geometric Distribution

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Theorem

Let $X$ be a discrete random variable with the geometric distribution with parameter $p$ for some $0 < p < 1$.

Formulation 1

$\map X \Omega = \set {0, 1, 2, \ldots} = \N$
$\map \Pr {X = k} = \paren {1 - p} p^k$


Then the excess kurtosis $\gamma_2$ of $X$ is given by:

$\gamma_2 = 6 + \dfrac {\paren {1 - p}^2} p$


Formulation 2

$\map X \Omega = \set {0, 1, 2, \ldots} = \N$
$\map \Pr {X = k} = p \paren {1 - p}^k$


Then the excess kurtosis $\gamma_2$ of $X$ is given by:

$\gamma_2 = 6 + \dfrac {p^2} {1 - p}$