Friday, 28 March 2014

elementary set theory - A question regarding joint cumulative probability distribution functions



Consider two random variables X and Y and their joint cumulative probability distribution function F. I'm attempting to show that $P\{a_1


My attempt
$$P\{a_1$$P(\{X>a_1\} \cap \{Xb_1\} \cap \{Y$$1 - P((\{X>a_1\} \cap \{Xb_1\} \cap \{Y$$1 - P(\{X>a_1\}^c \cup \{Xb_1\}^c \cup \{Y1P({Xa1}{Xa2}{Yb1}{Yb2})



So here I suppose I must apply the Inclusion–exclusion principle and becuase
{Xa1}, {Xa2} and {Yb1}, {Yb2} are respectively mutually exclusive we have that the terms will only be probabilities defined on single sets and on the intersection of two non-mutually exclusive sets. Despite of this it still seems a bit too cumbersome and I am not sure how to simplify the probabilities of intersections.




1P({Xa1})P({Xa2})P({Xb1})P({Xb2})
+P({Xa1}{Yb1})+P({Xa1}{Yb2})
+P({Xa2}{Yb1})+P({Xa2}{Yb2})



It just seems messy and I don't know how to continue. Am going in the right direction at least or am I completely off?


Answer



\begin{equation}
P(a_1\end{equation}




Also



\begin{equation}
P(X\end{equation}



\begin{equation}
P(X\end{equation}




And your result follows.


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