Function of Discrete Random Variable
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Theorem
Let $X$ be a discrete random variable on the probability space $\struct {\Omega, \Sigma, \Pr}$.
Let $g: \R \to \R$ be any real function.
Then $Y = g \sqbrk X$, defined as:
- $\forall \omega \in \Omega: \map Y \omega = g \sqbrk {\map X \omega}$
is also a discrete random variable.
Proof
As $\Img X$ is countable, then so is $\Img {g \sqbrk X}$.
Now consider $g^{-1} \sqbrk Y$.
We have that:
- $\forall x \in \R: \map {X^{-1} } x \in \Sigma$
We also have that:
- $\ds \forall y \in \R: \map {g^{-1} } y = \bigcup_{x: \map g x = y} \set x$
But $\Sigma$ is a sigma-algebra and therefore closed for unions.
Thus:
- $\forall y \in \R: \map {X^{-1} } {\map {g^{-1} } y} \in \Sigma$
Hence the result.
$\blacksquare$
Sources
- 1986: Geoffrey Grimmett and Dominic Welsh: Probability: An Introduction ... (previous) ... (next): $\S 2.3$: Functions of discrete random variables