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Expectation of a Function of a Random Variable

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Theorem
ProbabilityMeasureTheory

Discrete Given a discrete RV XX with range X\mathscr{X} and pmf pp, and given g:RRg:\mathbb{R}\to\mathbb{R}, then E[g(X)]=xXg(x) p(x)E[g(X)]=\sum_{x\in\mathscr{X}}g(x)\ p(x)Continuous Given a continuous RV XX with range X\mathscr{X} and pdf ff, and given g:RRg:\mathbb{R}\to\mathbb{R}, then E[g(X)]=Xg(x)f(x) dxE[g(X)]=\int_{\mathscr{X}} g(x)f(x) \ dx only if:E[g(X)]=g(x)f(x) dx<E[|g(X)|]=\int|g(x)|f(x) \ dx<\infty