Statistics Notation of probability distribution I am studying statistics but i'm a little unsure on the notation and I was wondering if anyone knew what this means when describing a probablity distribution? 
$$ X(\Omega, A, P) ->R $$ 
What do the $\Omega,A,P$ mean?
Thanks
 A: This is similar to other questions on the site. You are quoting standard notation to lead up to the definition of a specific random variable. (Some might criticize you for not finding them, but if you knew the key words for such a search, I doubt you would be asking this question.)
$\Omega$ is the sample space for a probability experiment; the set of all possible outcomes.
$A$ is a sigma-algebra of subsets of $\Omega$. One assigns probabilities to elements of $A$, sometimes called 'events.' In simple cases (e.g., where $\Omega$ is finite), it is typical for $A$ to be all subsets of $\Omega$.
However, for larger sample spaces $\Omega$ (e.g., the real line), it is not
possible to assign probabilities to all subsets of $\Omega$ in a manner
consistent with the Kolmogorov Axioms. The cure is to assign probabilities
only to 'events'. In practice, the sets in $A$ can include all 'events' of importance.
$P$ is a probability function. Its domain is $A$ (events) and its range is the interval $[0,1]$ on the real line.
$X$ is a random variable; it assigns real values to elements of $\Omega$.
Without having additional information about the notation and level of your text, I shouldn't say more for risk of adding to the confusion. I suggest you go back to the beginning of the chapter in which you found this relationship (or maybe the previous chapter) and trace through step by step to match my statements above to definitions in the text. I'm pretty sure this relationship didn't just spring up without some previous background
