Symmetric probability distribution

Thus the probability of being any given distance on one side of the value about which symmetry occurs is the same as the probability of being the same distance on the other side of that value.

A probability distribution is said to be symmetric if and only if there exists a value

The degree of symmetry, in the sense of mirror symmetry, can be evaluated quantitatively for multivariate distributions with the chiral index, which takes values in the interval [0;1], and which is null if and only if the distribution is mirror symmetric.

[1] Thus, a d-variate distribution is defined to be mirror symmetric when its chiral index is null.

The distribution can be discrete or continuous, and the existence of a density is not required, but the inertia must be finite and non null.

In the univariate case, this index was proposed as a non parametric test of symmetry.

[2] For continuous symmetric spherical, Mir M. Ali gave the following definition.

denote the class of spherically symmetric distributions of the absolutely continuous type in the n-dimensional Euclidean space having joint density of the form

inside a sphere with center at the origin with a prescribed radius which may be finite or infinite and zero elsewhere.

denotes a modified Bessel function of the second kind

Symmetric distribution for continuous probability distribution, specifically standard normal distribution, showcasing its perfect symmetry about the mean (0).
A symmetric discrete distribution, specifically a binomial distribution with 10 trials and a success probability of 0.5.