Symmetric probability distribution

In statistics, a symmetric probability distribution is a probability distribution—an assignment of probabilities to possible occurrences—which is unchanged when its probability density function or probability mass function is reflected around a vertical line at some value of the random variable represented by the distribution. This vertical line is the line of symmetry of the 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. In statistics, a symmetric probability distribution is a probability distribution—an assignment of probabilities to possible occurrences—which is unchanged when its probability density function or probability mass function is reflected around a vertical line at some value of the random variable represented by the distribution. This vertical line is the line of symmetry of the 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 x 0 {displaystyle x_{0}} such that where f is the probability density function if the distribution is continuous or the probability mass function if the distribution is discrete. For continuous symmetric spherical, Mir M. Ali gave the following definition. Let F {displaystyle {mathcal {F}}} denote the class of spherically symmetric distributions of the absolutely continuous type in the n-dimensional Euclidean space having joint density of the form f ( x 1 , x 2 , … , x n ) = g ( x 1 2 + x 1 2 + ⋯ + x n 2 ) {displaystyle f(x_{1},x_{2},dots ,x_{n})=g(x_{1}^{2}+x_{1}^{2}+dots +x_{n}^{2})} inside a sphere with center at the origin with a prescribed radius which may be finite or infinite and zero elsewhere. Typically a symmetric continuous distribution's probability density function contains the index value x {displaystyle x} only in the context of a term ( x − x 0 ) 2 k {displaystyle (x-x_{0})^{2k}} where k {displaystyle k} is some positive integer (usually 1). This quadratic or other even-powered term takes on the same value for x = x 0 − δ {displaystyle x=x_{0}-delta } as for x = x 0 + δ {displaystyle x=x_{0}+delta } , giving symmetry about x 0 {displaystyle x_{0}} . Sometimes the density function contains the term | x − x 0 | {displaystyle |x-x_{0}|} , which also shows symmetry about x 0 . {displaystyle x_{0}.}