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lectures/prob_dist.md
@@ -156,13 +156,15 @@ Check that your answers agree with `u.mean()` and `u.var()`.
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#### Bernoulli distribution
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Another useful distribution is the Bernoulli distribution on $S = \{0,1\}$, which has PMF:
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$$
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p(x_i)=
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\begin{cases}
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p & \text{if $x_i = 1$}\\
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1-p & \text{if $x_i = 0$}
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\end{cases}
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Here $x_i \in S$ is the outcome of the random variable.
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We can import the Bernoulli distribution on $S = \{0,1\}$ from SciPy like so:
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