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When negative ('left-skewed'): the left tail is longer; the mass of the distribution is concentrated on the right of a histogram. When positive ('right-skewed'): the right tail is longer; the mass of the distribution is concentrated on the left of a histogram. A normal distribution has a skewness of 0."><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@univgroningen"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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<h1>Skewness of the Sample</h1>
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<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/skewness.R" class="external-link"><code>R/skewness.R</code></a></small>
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<div class="hidden name"><code>skewness.Rd</code></div>
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</div>
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<div class="ref-description">
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<p>Skewness is a measure of the asymmetry of the probability distribution of a real-valued random variable about its mean.</p>
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<p>When negative ('left-skewed'): the left tail is longer; the mass of the distribution is concentrated on the right of a histogram. When positive ('right-skewed'): the right tail is longer; the mass of the distribution is concentrated on the left of a histogram. A normal distribution has a skewness of 0.</p>
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<div id="ref-usage">
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<div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">skewness</span><span class="op">(</span><span class="va">x</span>, na.rm <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
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<span class="co"># S3 method for default</span>
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<span class="fu">skewness</span><span class="op">(</span><span class="va">x</span>, na.rm <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
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<span class="co"># S3 method for matrix</span>
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<span class="fu">skewness</span><span class="op">(</span><span class="va">x</span>, na.rm <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>
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<span class="co"># S3 method for data.frame</span>
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<span class="fu">skewness</span><span class="op">(</span><span class="va">x</span>, na.rm <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></code></pre></div>
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</div>
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<div id="arguments">
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<h2>Arguments</h2>
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<dl><dt>x</dt>
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<dd><p>a vector of values, a <a href="https://rdrr.io/r/base/matrix.html" class="external-link">matrix</a> or a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></p></dd>
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<dt>na.rm</dt>
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<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> value indicating whether <code>NA</code> values should be stripped before the computation proceeds</p></dd>
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</dl></div>
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<h2>Stable Lifecycle</h2>
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<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
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The <a href="lifecycle.html">lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
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<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
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<h2>Read more on Our Website!</h2>
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<p>On our website <a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR/</a> you can find <a href="https://msberends.github.io/AMR/articles/AMR.html">a comprehensive tutorial</a> about how to conduct AMR data analysis, the <a href="https://msberends.github.io/AMR/reference/">complete documentation of all functions</a> and <a href="https://msberends.github.io/AMR/articles/WHONET.html">an example analysis using WHONET data</a>.</p>
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<h2>See also</h2>
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<div class="dont-index"><p><code><a href="kurtosis.html">kurtosis()</a></code></p></div>
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