The expectation is the “weighted sum” of the “possible values” that X can take on. Discrete The expectation or expected value of a discrete RVX with range X and pmfp is E[X]=x∈X∑xp(x)=x∈X∑xP(X=x)Continuous The expectation or expected value of a continuous RVX with range X and pdff is E[X]=Ω∫XdP=∫Xxf(x)dxonly if:E[∣X∣]=∫∣x∣f(x)dx<∞ i.e. X is integrable or X∈L1(Ω,F,P).
MCT: Let (Xn)n∈N be a sequence of rvs where Xn≥0,∀n∈N and Xn↑X as n→∞ then E[Xn]↑E[X] as n→∞
Fatou’s Lemma: Let (Xn)n∈N be rv where Xn≥0,∀n∈N then E[n→∞liminfXn]≤n→∞liminfE[Xn]
Dominated Convergence Theorem: Let (Xn)n∈N⊂L1(Ω,F,P), let Y∈L1(Ω,F,P) and assume ∣Xn∣≤Y,∀n∈N. Let X:Ω→R s.t. Xn→X. Let G⊂F sub-σ-algebra. Then X∈L1and E[Xn∣G]L1E[X∣G]
Lemma
Let f:X→R, g:Y→R. If X and Y are independent, E[f(X)g(Y)]=E[f(X)]E[g(Y)]