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How do you compute the expected value of a random variable? The problem I found asks; $$ W = rV^3$$ where $r$ is a constant and $V$ is a normally distributed random variable with mean 6 and standard deviation 1. How can I compute $E[W]$?

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Write $V = \mu + \sigma Z$, where $Z$ is the standard normal random variable. Then $$ \mathbb{E}(W) = r \mathbb{E}\left( \left(\mu + \sigma Z\right)^3 \right) = r \left( \mu^3 +3 \mu^2 \sigma \mathbb{E}(Z) + 3 \mu \sigma^2 \mathbb{E}(Z^2) + \sigma^3 \mathbb{E}(Z^3) \right) $$ Since $Z$ is symmetric, i.e. $Z \stackrel{d}{=} -Z$, it follows that $\mathbb{E}(Z) = 0$ and $\mathbb{E}(Z^3)=0$. It only remains to evaluate $$ \mathbb{E}(Z^2) = \int_{-\infty}^\infty z^2 \frac{1}{\sqrt{2\pi}} \mathrm{e}^{-z^2/2} \mathrm{d} z = \sqrt{\frac{2}{\pi}} \int_0^\infty z^2 \mathrm{e}^{-z^2/2} \mathrm{d} z \stackrel{z^2 = x}{=} \frac{1}{\sqrt{2\pi}} \underbrace{\int_0^\infty \sqrt{x} \mathrm{e}^{-x/2} \mathrm{d} x}_{2^{3/2} \Gamma(3/2) = \sqrt{2\pi}} = 1 $$ Now combine these results to readily obtain $\mathbb{E}(W)$.

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    $\begingroup$ +1 To avoid the integral, note that $\mathbb{E}(Z^2)$ is the sum of its variance and the square of its mean, i.e. (as $Z$ has a standard normal distribution) $1+0^2=1$. $\endgroup$
    – Henry
    Oct 19 '12 at 7:03
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$E[W] = rE[V^{3}]$ since $r$ is a constant. You can obtain the information about higher moments of the normal distribution here http://en.wikipedia.org/wiki/Normal_distribution See "Raw moment"

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  • $\begingroup$ My class isn't cover moment functions. Is there any way to understand it without knowledge of moment functions? There should be, since it's on our outline $\endgroup$ Oct 19 '12 at 2:29
  • $\begingroup$ Maybe you don't need to know how to compute it, but are you allowed to use that information? I can't see how you can obtain the third moment otherwise. $\endgroup$
    – Ken Dunn
    Oct 19 '12 at 2:33

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