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@ -60,6 +60,9 @@ As a function, $\mathcal{H}$ maps values in $\Omega$ to values in $\mathbb{Z}^+_
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\item ...and so on.
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\end{itemize}
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Intuitively, a random variable assigns a \say{value} in $\mathbb{R}$ to every possible outcome.
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\definition{}
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We can compute the probability that a random variable takes a certain value by computing the probability of
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the set of outcomes that produce that value. \par
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@ -92,18 +95,18 @@ Find $\mathcal{P}(\mathcal{X} = x)$ for all $x$ in $\mathbb{Z}$.
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%
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\definition{}
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\definition{}<defexp>
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Say we have a random variable $\mathcal{X}$ that produces outputs in $\mathbb{R}$. \par
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The \textit{expected value} of $\mathcal{X}$ is then defined as
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\begin{equation*}
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\mathcal{E}(\mathcal{X})
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~\coloneqq~ \sum_{x \in A}\Bigl(x \times \mathcal{P}\bigl(\mathcal{X} = x\bigr)\Bigr)
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~\coloneqq~ \sum_{x \in \mathbb{R}}\Bigl(x \times \mathcal{P}\bigl(\mathcal{X} = x\bigr)\Bigr)
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~=~ \sum_{\omega \in \Omega}\Bigl(\mathcal{X}(\omega) \times \mathcal{P}(\omega)\Bigr)
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\end{equation*}
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That is, $\mathcal{E}(\mathcal{X})$ is the average of all possible outputs of $\mathcal{X}$ weighted by their probability.
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\problem{}
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Say we flip a coin with $\mathcal{P}(\texttt{H}) = \nicefrac{1}{3}$ three times. \par
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Say we flip a coin with $\mathcal{P}(\texttt{H}) = \nicefrac{1}{3}$ two times. \par
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Define $\mathcal{H}$ as the number of heads we see. \par
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Find $\mathcal{E}(\mathcal{H})$.
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@ -113,6 +116,14 @@ Find $\mathcal{E}(\mathcal{H})$.
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Let $\mathcal{A}$ and $\mathcal{B}$ be two random variables. \par
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Show that $\mathcal{E}(\mathcal{A} + \mathcal{B}) = \mathcal{E}(\mathcal{A}) + \mathcal{E}(\mathcal{B})$.
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\begin{solution}
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Use the second definition of $\mathcal{E}$, $\sum_{\omega \in \Omega}\Bigl(\mathcal{X}(\omega) \times \mathcal{P}(\omega)\Bigr)$.
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\vspace{2mm}
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Make sure students understand all parts of \ref{defexp}, and are comfortable with the fact that a random variable \say{assigns values} to outcomes.
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\end{solution}
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\vfill
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\definition{}
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