Expectation over Gaussian random variable with mean zero and finite variance

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Can someone explain me how is the expectation of a random variable (say $X$) calculated over Gaussian random variable with mean zero and a finite variance $\varepsilon\sim\mathcal{N}(0,\sigma^{2})$ ?. And what does it intuitively mean to calculate expectation of a random variable over a different random variable $E_\varepsilon(X)$, which in this case is $\varepsilon\sim\mathcal{N}(0,\sigma^2)$ ?