Conditional Probability Defines Probability Space

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Theorem

Let $\left({\Omega, \Sigma, \Pr}\right)$ be a measure space.

Let $B \in \Sigma$ such that $\Pr \left({B}\right) > 0$.


Let $Q: \Sigma \to \R$ be the real-valued function defined as:

$Q \left({A}\right) = \Pr \left({A \mid B}\right)$

where:

$\Pr \left({A \mid B}\right) = \dfrac {\Pr \left({A \cap B}\right)}{\Pr \left({B}\right)}$

is the conditional probability of $A$ given $B$.


Then $\left({\Omega, \Sigma, \Pr}\right)$ is a probability space.


Proof

To prove this assertion we need to show that $Q$ is a probability measure on $\left({\Omega, \Sigma}\right)$.


As $\Pr$ is a measure, we have that:

$\forall A \in \Omega: Q \left({A}\right) \ge 0$

Also, we have that:

\(\displaystyle \) \(\displaystyle \) \(\displaystyle \) \(\displaystyle Q \left({\Omega}\right)\) \(=\) \(\displaystyle \Pr \left({\Omega \mid B}\right)\) \(\displaystyle \) \(\displaystyle \) \(\displaystyle \)                    
\(\displaystyle \) \(\displaystyle \) \(\displaystyle \) \(\displaystyle \) \(=\) \(\displaystyle \frac {\Pr \left({\Omega \cap B}\right)}{\Pr \left({B}\right)}\) \(\displaystyle \) \(\displaystyle \) \(\displaystyle \)                    
\(\displaystyle \) \(\displaystyle \) \(\displaystyle \) \(\displaystyle \) \(=\) \(\displaystyle \frac {\Pr \left({B}\right)}{\Pr \left({B}\right)}\) \(\displaystyle \) \(\displaystyle \) \(\displaystyle \)          Intersection with Universe          
\(\displaystyle \) \(\displaystyle \) \(\displaystyle \) \(\displaystyle \) \(=\) \(\displaystyle 1\) \(\displaystyle \) \(\displaystyle \) \(\displaystyle \)          as $\Pr \left({B}\right) > 0$          


Now, suppose that $A_1, A_2, \ldots$ are disjoint events in $\Sigma$.

Then:

\(\displaystyle \) \(\displaystyle \) \(\displaystyle \) \(\displaystyle Q \left({\bigcup_i A_i}\right)\) \(=\) \(\displaystyle \frac 1 {\Pr \left({B}\right)} \Pr \left({\left({\bigcup_i A_i}\right) \cap B}\right)\) \(\displaystyle \) \(\displaystyle \) \(\displaystyle \)                    
\(\displaystyle \) \(\displaystyle \) \(\displaystyle \) \(\displaystyle \) \(=\) \(\displaystyle \frac 1 {\Pr \left({B}\right)} \Pr \left({\bigcup_i A_i}\right) \left({A_i \cap B}\right)\) \(\displaystyle \) \(\displaystyle \) \(\displaystyle \)          Intersection Distributes over Union          
\(\displaystyle \) \(\displaystyle \) \(\displaystyle \) \(\displaystyle \) \(=\) \(\displaystyle \frac {\Pr \left({B}\right)}{\sum \Pr \left({A_i \cap B}\right)}\) \(\displaystyle \) \(\displaystyle \) \(\displaystyle \)          as $\Pr$ satisfies the Kolmogorov axioms          
\(\displaystyle \) \(\displaystyle \) \(\displaystyle \) \(\displaystyle \) \(=\) \(\displaystyle \sum Q \left({A_i}\right)\) \(\displaystyle \) \(\displaystyle \) \(\displaystyle \)          by definition.          

$\blacksquare$


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