Definition:Degenerate Distribution
Jump to navigation
Jump to search
Definition
Let $X$ be a discrete random variable on a probability space.
Then $X$ has a degenerate distribution with parameter $r$ if and only if:
- $\Omega_X = \set r$
- $\map \Pr {X = k} = \begin {cases} 1 & : k = r \\ 0 & : k \ne r \end {cases}$
That is, there is only value that $X$ can take, namely $r$, which it takes with certainty.
![]() | This page or section has statements made on it that ought to be extracted and proved in a Theorem page. You can help $\mathsf{Pr} \infty \mathsf{fWiki}$ by creating any appropriate Theorem pages that may be needed. To discuss this page in more detail, feel free to use the talk page. |
It trivially gives rise to a probability mass function satisfying $\map \Pr \Omega = 1$.
Equally trivially, it has an expectation of $r$ and a variance of $0$.
Also see
- Results about the degenerate distribution can be found here.