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stats.html
<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<title>Statistical functions (scipy.stats) &mdash; SciPy v0.16.0 Reference Guide</title>
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var DOCUMENTATION_OPTIONS = {
URL_ROOT: './',
VERSION: '0.16.0',
COLLAPSE_INDEX: false,
FILE_SUFFIX: '.html',
HAS_SOURCE: false
};
</script>
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<li class="active"><a href="index.html">SciPy v0.16.0 Reference Guide</a></li>
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<h3><a href="index.html">Table Of Contents</a></h3>
<ul>
<li><a class="reference internal" href="#">Statistical functions (<code class="docutils literal"><span class="pre">scipy.stats</span></code>)</a><ul>
<li><a class="reference internal" href="#continuous-distributions">Continuous distributions</a></li>
<li><a class="reference internal" href="#multivariate-distributions">Multivariate distributions</a></li>
<li><a class="reference internal" href="#discrete-distributions">Discrete distributions</a></li>
<li><a class="reference internal" href="#statistical-functions">Statistical functions</a><ul>
</ul>
</li>
<li><a class="reference internal" href="#circular-statistical-functions">Circular statistical functions</a></li>
<li><a class="reference internal" href="#contingency-table-functions">Contingency table functions</a></li>
<li><a class="reference internal" href="#plot-tests">Plot-tests</a></li>
<li><a class="reference internal" href="#masked-statistics-functions">Masked statistics functions</a></li>
<li><a class="reference internal" href="#univariate-and-multivariate-kernel-density-estimation-scipy-stats-kde">Univariate and multivariate kernel density estimation (<code class="docutils literal"><span class="pre">scipy.stats.kde</span></code>)</a></li>
</ul>
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<h4>Previous topic</h4>
<p class="topless"><a href="generated/scipy.special.xlog1py.html"
title="previous chapter">scipy.special.xlog1py</a></p>
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<p class="topless"><a href="generated/scipy.stats.contingency.expected_freq.html"
title="next chapter">scipy.stats.contingency.expected_freq</a></p>
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<span class="target" id="module-scipy.stats"></span><div class="section" id="module-scipy.stats">
<span id="statistical-functions-scipy-stats"></span><h1>Statistical functions (<a class="reference internal" href="#module-scipy.stats" title="scipy.stats"><code class="xref py py-mod docutils literal"><span class="pre">scipy.stats</span></code></a>)<a class="headerlink" href="#module-scipy.stats" title="Permalink to this headline">¶</a></h1>
<p>This module contains a large number of probability distributions as
well as a growing library of statistical functions.</p>
<p>Each univariate distribution is an instance of a subclass of <a class="reference internal" href="generated/scipy.stats.rv_continuous.html#scipy.stats.rv_continuous" title="scipy.stats.rv_continuous"><code class="xref py py-obj docutils literal"><span class="pre">rv_continuous</span></code></a>
(<a class="reference internal" href="generated/scipy.stats.rv_discrete.html#scipy.stats.rv_discrete" title="scipy.stats.rv_discrete"><code class="xref py py-obj docutils literal"><span class="pre">rv_discrete</span></code></a> for discrete distributions):</p>
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<div class="section" id="continuous-distributions">
<h2>Continuous distributions<a class="headerlink" href="#continuous-distributions" title="Permalink to this headline">¶</a></h2>
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<col width="10%" />
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<div class="section" id="multivariate-distributions">
<h2>Multivariate distributions<a class="headerlink" href="#multivariate-distributions" title="Permalink to this headline">¶</a></h2>
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<div class="section" id="discrete-distributions">
<h2>Discrete distributions<a class="headerlink" href="#discrete-distributions" title="Permalink to this headline">¶</a></h2>
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<div class="section" id="statistical-functions">
<h2>Statistical functions<a class="headerlink" href="#statistical-functions" title="Permalink to this headline">¶</a></h2>
<p>Several of these functions have a similar version in scipy.stats.mstats
which work for masked arrays.</p>
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</div>
<div class="section" id="circular-statistical-functions">
<h2>Circular statistical functions<a class="headerlink" href="#circular-statistical-functions" title="Permalink to this headline">¶</a></h2>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%" />
<col width="90%" />
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</div>
<div class="section" id="contingency-table-functions">
<h2>Contingency table functions<a class="headerlink" href="#contingency-table-functions" title="Permalink to this headline">¶</a></h2>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%" />
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<tr class="row-odd"><td><a class="reference internal" href="generated/scipy.stats.contingency.expected_freq.html#scipy.stats.contingency.expected_freq" title="scipy.stats.contingency.expected_freq"><code class="xref py py-obj docutils literal"><span class="pre">contingency.expected_freq</span></code></a>(observed)</td>
<td>Compute the expected frequencies from a contingency table.</td>
</tr>
<tr class="row-even"><td><a class="reference internal" href="generated/scipy.stats.contingency.margins.html#scipy.stats.contingency.margins" title="scipy.stats.contingency.margins"><code class="xref py py-obj docutils literal"><span class="pre">contingency.margins</span></code></a>(a)</td>
<td>Return a list of the marginal sums of the array <em class="xref py py-obj">a</em>.</td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="plot-tests">
<h2>Plot-tests<a class="headerlink" href="#plot-tests" title="Permalink to this headline">¶</a></h2>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%" />
<col width="90%" />
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</table>
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<div class="section" id="masked-statistics-functions">
<h2>Masked statistics functions<a class="headerlink" href="#masked-statistics-functions" title="Permalink to this headline">¶</a></h2>
<div class="toctree-wrapper compound">
<ul>
<li class="toctree-l1"><a class="reference internal" href="stats.mstats.html">Statistical functions for masked arrays (<code class="docutils literal"><span class="pre">scipy.stats.mstats</span></code>)</a><ul class="simple">
</ul>
</li>
</ul>
</div>
</div>
<div class="section" id="univariate-and-multivariate-kernel-density-estimation-scipy-stats-kde">
<h2>Univariate and multivariate kernel density estimation (<code class="xref py py-mod docutils literal"><span class="pre">scipy.stats.kde</span></code>)<a class="headerlink" href="#univariate-and-multivariate-kernel-density-estimation-scipy-stats-kde" title="Permalink to this headline">¶</a></h2>
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<p>For many more stat related functions install the software R and the
interface package rpy.</p>
</div>
</div>
<div class="toctree-wrapper compound">
</div>
</div>
</div>
</div>
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&copy; Copyright 2008-2014, The Scipy community.
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Last updated on Sep 23, 2015.
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Created using <a href="http://sphinx.pocoo.org/">Sphinx</a> 1.3.1.
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