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Symmetric Distribution

Definition

Let XX be a random variable and let a∈Ra\in\mathbb{R}. The distribution of XX is symmetric about aa if X−aX-a and a−Xa-X have the same distribution.


Interpretation

A distribution is symmetric about aa when deviations below aa behave exactly like deviations above aa: XX is as likely to fall at least a distance tt below aa as at least a distance tt above it. The graph of the PMF or density is then a mirror image in the vertical line at aa.

A density symmetric about a point a, with equal shaded tails below a - t and above a + t.

The density in the figure is symmetric about aa, so fX(a−t)=fX(a+t)f_X(a-t)=f_X(a+t) for every tt, and the two shaded tails P(X≤a−t)\mathbb{P}(X\le a-t) and P(X≥a+t)\mathbb{P}(X\ge a+t) have the same area. This holds for every distance tt, not just the one drawn.

In the Definition, X−aX-a is the deviation above aa and a−Xa-X the deviation below it; symmetry says that the two have the same distribution. An equivalent condition is P(X≤a−t)=P(X≥a+t)\mathbb{P}(X\le a-t)=\mathbb{P}(X\ge a+t) for all tt. With a=0a=0 and the standard normal distribution, this is the identity Φ(−z)=1−Φ(z)\Phi(-z)=1-\Phi(z).

Symmetry fixes the centre. The point aa is a median: P(X≤a)=P(X≥a)\mathbb{P}(X\le a)=\mathbb{P}(X\ge a), and the two add up to at least 11, so each is at least 12\tfrac{1}{2}. If the mean exists, it equals aa, since linearity gives E[X−a]=E[a−X]=−E[X−a]\mathbb{E}[X-a]=\mathbb{E}[a-X]=-\mathbb{E}[X-a], so E[X−a]=0\mathbb{E}[X-a]=0.

The converse fails: mean and median can coincide for a distribution that is not symmetric. Symmetry is also not special to the normal distribution; the uniform distribution on (a−c,a+c)(a-c,a+c) and a fair die, symmetric about 3.53.5, are symmetric too.


Key Results

  • Symmetry about a centre means left and right deviations have the same distribution.
  • If the distribution is symmetric about aa, then aa is a median, and the mean equals aa whenever it exists.
  • A symmetric distribution need not be normal.

Examples

  • A normal distribution is symmetric about its mean.
  • A fair die distribution is symmetric around three and a half.
  • A two-point distribution with equal mass at negative one and one is symmetric about zero.

Prerequisites

Sources

Aliases: symmetry of a random variable, symmetric random variable Keywords: distribution symmetric about a point Symbols: element of, phi, real numbers

Last updated: 20 October 2026 03:02