User:Caliburn/s/prob/Expectation is Monotone
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Theorem
Let $\struct {\Omega, \Sigma, \Pr}$ be a probability space.
Let $X$ and $Y$ be integrable random variables on $\struct {\Omega, \Sigma, \Pr}$ such that:
- $\map X \omega \le \map Y \omega$
for each $\omega \in \Omega$.
Then:
- $\expect X \le \expect Y$
Proof
From Pointwise Difference of Measurable Functions is Measurable, we have:
- $Y - X$ is $\Sigma$-measurable.
From Integral of Integrable Function is Additive: Corollary 2, we have:
- $Y - X$ is integrable.
We also have:
- $\map {\paren {Y - X} } \omega \ge 0$ for each $\omega \in \Omega$.
So, from Expectation of Non-Negative Random Variable is Non-Negative: Corollary, we have:
- $\expect {Y - X} \ge 0$
From Expectation is Linear we then obtain:
- $\expect Y - \expect X \ge 0$
that is:
- $\expect X \le \expect Y$