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<title>GNU Scientific Library – Reference Manual: Absolute deviation</title>
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<a name="Absolute-deviation"></a>
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Next: <a href="Higher-moments-_0028skewness-and-kurtosis_0029.html#Higher-moments-_0028skewness-and-kurtosis_0029" accesskey="n" rel="next">Higher moments (skewness and kurtosis)</a>, Previous: <a href="Mean-and-standard-deviation-and-variance.html#Mean-and-standard-deviation-and-variance" accesskey="p" rel="previous">Mean and standard deviation and variance</a>, Up: <a href="Statistics.html#Statistics" accesskey="u" rel="up">Statistics</a> [<a href="Function-Index.html#Function-Index" title="Index" rel="index">Index</a>]</p>
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<a name="Absolute-deviation-1"></a>
<h3 class="section">21.2 Absolute deviation</h3>
<dl>
<dt><a name="index-gsl_005fstats_005fabsdev"></a>Function: <em>double</em> <strong>gsl_stats_absdev</strong> <em>(const double <var>data</var>[], size_t <var>stride</var>, size_t <var>n</var>)</em></dt>
<dd><p>This function computes the absolute deviation from the mean of
<var>data</var>, a dataset of length <var>n</var> with stride <var>stride</var>. The
absolute deviation from the mean is defined as,
where <em>x_i</em> are the elements of the dataset <var>data</var>. The
absolute deviation from the mean provides a more robust measure of the
width of a distribution than the variance. This function computes the
mean of <var>data</var> via a call to <code>gsl_stats_mean</code>.
</p></dd></dl>
<dl>
<dt><a name="index-gsl_005fstats_005fabsdev_005fm"></a>Function: <em>double</em> <strong>gsl_stats_absdev_m</strong> <em>(const double <var>data</var>[], size_t <var>stride</var>, size_t <var>n</var>, double <var>mean</var>)</em></dt>
<dd><p>This function computes the absolute deviation of the dataset <var>data</var>
relative to the given value of <var>mean</var>,
This function is useful if you have already computed the mean of
<var>data</var> (and want to avoid recomputing it), or wish to calculate the
absolute deviation relative to another value (such as zero, or the
median).
</p></dd></dl>
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