MHB Conditional expected value (using measure theory)

AI Thread Summary
The discussion focuses on proving the property that the expected value of the conditional expectation equals the expected value of the original random variable, specifically that E(E(X|G)) = E(X). The user attempts to utilize the definition of conditional expected value through the relationship E(I_hE(X|G)) = E(I_hX) for every h in G. They establish that if Z = E(X|G), then Z is G-measurable, leading to the conclusion that E[Z] = E[X]. The proof confirms the validity of the property using measure theory principles.
Barioth
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Hi, I'm trying to show that
Givien a probability triplet $$(\theta,F,P)$$
with $$G\in F$$ a sub sigma algebra
$$E(E(X|G))=E(X)$$

Now I want to use $$E(I_hE(X|G))=E(I_hX)$$
for every $$h\in G $$

since that's pretty much all I've for the definition of conditional expected value.

I know this property should use the definition of expected value, but I can't get it to work.

Thanks
 
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Let $\mathcal{G} \subset \mathcal{F}$ be a sub $\sigma$-algebra of $\mathcal{F}$ then we have to prove:
$$\mathbb{E}[\mathbb{E}[X|\mathcal{G}]] = \mathbb{E}[X]$$

Set $Z = \mathbb{E}[X|\mathcal{G}]$ then by definition $Z$ is $\mathcal{G}$-measurable and $\forall G \in \mathcal{G}: \mathbb{E}[ZI_G] = \mathbb{E}[XI_G]$. Since $\mathcal{G}$ is a sub $\sigma$-algebra it has to contain $\Omega$ thus in particular $\mathbb{E}[ZI_{\Omega}] = \mathbb{E}[XI_{\Omega}]$ which means $\mathbb{E}[Z] = \mathbb{E}[X]$. Hence $\mathbb{E}[Z] = \mathbb{E}[\mathbb{E}[X|\mathcal{G}]] = \mathbb{E}[X]$.
 
Thanks, very clean!
 
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