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<div class="title">RANDBIN Generate Binomial Random Variables </div> </div>
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<div class="textblock"><p>Section: <a class="el" href="sec_random.html">Random Number Generation</a> </p>
<h1><a class="anchor" id="Usage"></a>
Usage</h1>
<p>Generates random variables with a binomial distribution. The general syntax for its use is </p>
<pre class="fragment"> y = randbin(N,p)
</pre><p> where <code>N</code> is a vector representing the number of Bernoulli trials, and <code>p</code> is the success probability associated with each trial. </p>
<h1><a class="anchor" id="Function"></a>
Internals</h1>
<p>A Binomial random variable describes the number of successful outcomes from <code>N</code> Bernoulli trials, with the probability of success in each trial being <code>p</code>. The probability distribution is </p>
<p class="formulaDsp">
<img class="formulaDsp" alt="\[ P(n) = \frac{N!}{n!(N-n)!}p^n(1-p)^{N-n} \]" src="form_139.png"/>
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<h1><a class="anchor" id="Example"></a>
Example</h1>
<p>Here we generate <code>10</code> binomial random variables, corresponding to <code>N=100</code> trials, each with probability <code>p=0.1</code>, using both <code>randbin</code> and then again using <code>rand</code> (to simulate the trials):</p>
<pre class="fragment">--> randbin(100,.1*ones(1,10))
ans =
6 7 6 7 13 7 7 10 13 15
--> sum(rand(100,10)<0.1)
ans =
11 9 8 9 15 16 11 17 4 7
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