Law of total probability: decomposing expectation over countable events
Dependencies:
- Random variable
- Conditional expectation
- /measure-theory/linearity-of-lebesgue-integral
$\newcommand{\E}{\operatorname{E}}$ There are many results that are called 'Law of total probability'. The following is one of them.
Let $S$ be a countable set of pairwise-disjoint events such that $\bigcup_{A \in S} A = \Omega$ and $\Pr(\cdot \mid A)$ is defined $\forall A \in S$. Let $X$ be a random variable. Then \[ \E(X) = \sum_{A \in S} \E(X \mid A)\Pr(A). \]
Proof
\begin{align} \E(X) &= \int_{\omega \subseteq \Omega} X(\omega)\Pr(\omega) \\ &= \int_{\omega \subseteq \Omega} X(\omega)\left(\sum_{A \in S} \Pr(\omega \cap A)\right) \\ &= \int_{\omega \subseteq \Omega} X(\omega)\left(\sum_{A \in S} \Pr(\omega \mid A) \Pr(A)\right) \\ &= \sum_{A \in S} \Pr(A)\left(\int_{\omega \subseteq \Omega} X(\omega)\Pr(\omega \mid A)\right) \tag{linearity of Lebesgue integral} \\ &= \sum_{A \in S} \Pr(A)\E(X \mid A) \end{align}
Dependency for: None
Info:
- Depth: 8
- Number of transitive dependencies: 21
Transitive dependencies:
- /analysis/topological-space
- /sets-and-relations/countable-set
- /sets-and-relations/de-morgan-laws
- /measure-theory/linearity-of-lebesgue-integral
- /measure-theory/lebesgue-integral
- σ-algebra
- Generated σ-algebra
- Borel algebra
- Measurable function
- Generators of the real Borel algebra (incomplete)
- Measure
- σ-algebra is closed under countable intersections
- Group
- Ring
- Field
- Vector Space
- Probability
- Conditional probability (incomplete)
- Random variable
- Expected value of a random variable
- Conditional expectation