Definition:Kurtosis

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Definition

Let $X$ be a random variable with mean $\mu$ and standard deviation $\sigma$.

The kurtosis of $X$ is a measure of the concentration of $X$ about its expectation.

Definition 1

The kurtosis of $X$ is the fourth standardized moment of $X$:

$\alpha_4 = \expect {\paren {\dfrac {X - \mu} \sigma}^4}$

where $\expect {\, \cdot \,}$ denotes expectation.


Definition 2

The kurtosis of $X$ is defined as:

$\alpha_4 = \dfrac {\mu_4} {\paren {\mu_2}^2}$

where $\mu_i$ denotes the $i$th central moment of $X$.


Coefficient of Kurtosis

Let $X$ be a random variable with mean $\mu$ and standard deviation $\sigma$.

The coefficient of kurtosis of $X$ is the coefficient:

$\gamma_2 = \dfrac {\mu_4} { {\mu_2}^2} - 3$

where $\mu_i$ denotes the $i$th central moment of $X$.


Notation

The kurtosis of $X$ is usually denoted $\alpha_4$.

Some sources denote the kurtosis by the symbol $\Beta_2$ or $\beta_2$.


Platykurtic

A random variable with kurtosis less than $3$ is described as platykurtic.


Mesokurtic

Let $X$ be a random variable with kurtosis equal to $3$.

Then $X$ is described as mesokurtic.


Leptokurtic

A random variable with kurtosis greater than $3$ is described as leptokurtic.


Incorrect Definition

The kurtosis of a random variable is often seen described as a measure of how steep the peak is at the mean or the mode.

However, this is incorrect.

It is more accurate to describe it as a measure of how heavy or fat the tails are.


Also see

  • Results about kurtosis can be found here.


Linguistic Note

The word kurtosis derives from the Greek κυρτός (kyrtos or kurtos), meaning curved or arching.


Sources