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<h3 class="section">25.3 Statistical Plots</h3>
<!-- Should hist be moved to here, or perhaps the qqplot and ppplot -->
<!-- functions should be moved to the Plotting Chapter? -->
<p>Octave can create Quantile Plots (QQ-Plots), and Probability Plots
(PP-Plots). These are simple graphical tests for determining if a
data set comes from a certain distribution.
<p>Note that Octave can also show histograms of data
using the <code>hist</code> function as described in
<a href="Two_002dDimensional-Plots.html#Two_002dDimensional-Plots">Two-Dimensional Plots</a>.
<!-- ./statistics/base/qqplot.m -->
<p><a name="doc_002dqqplot"></a>
<div class="defun">
— Function File: [<var>q</var>, <var>s</var>] = <b>qqplot</b> (<var>x, dist, params</var>)<var><a name="index-qqplot-1863"></a></var><br>
<blockquote><p>Perform a QQ-plot (quantile plot).
<p>If F is the CDF of the distribution <var>dist</var> with parameters
<var>params</var> and G its inverse, and <var>x</var> a sample vector of length
<var>n</var>, the QQ-plot graphs ordinate <var>s</var>(<var>i</var>) = <var>i</var>-th
largest element of x versus abscissa <var>q</var>(<var>i</var>f) = G((<var>i</var> -
0.5)/<var>n</var>).
<p>If the sample comes from F except for a transformation of location
and scale, the pairs will approximately follow a straight line.
<p>The default for <var>dist</var> is the standard normal distribution. The
optional argument <var>params</var> contains a list of parameters of
<var>dist</var>. For example, for a quantile plot of the uniform
distribution on [2,4] and <var>x</var>, use
<pre class="example"> qqplot (x, "uniform", 2, 4)
</pre>
<p class="noindent"><var>dist</var> can be any string for which a function <var>dist_inv</var>
that calculates the inverse CDF of distribution <var>dist</var> exists.
<p>If no output arguments are given, the data are plotted directly.
</p></blockquote></div>
<!-- ./statistics/base/ppplot.m -->
<p><a name="doc_002dppplot"></a>
<div class="defun">
— Function File: [<var>p</var>, <var>y</var>] = <b>ppplot</b> (<var>x, dist, params</var>)<var><a name="index-ppplot-1864"></a></var><br>
<blockquote><p>Perform a PP-plot (probability plot).
<p>If F is the CDF of the distribution <var>dist</var> with parameters
<var>params</var> and <var>x</var> a sample vector of length <var>n</var>, the
PP-plot graphs ordinate <var>y</var>(<var>i</var>) = F (<var>i</var>-th largest
element of <var>x</var>) versus abscissa <var>p</var>(<var>i</var>) = (<var>i</var> -
0.5)/<var>n</var>. If the sample comes from F, the pairs will
approximately follow a straight line.
<p>The default for <var>dist</var> is the standard normal distribution. The
optional argument <var>params</var> contains a list of parameters of
<var>dist</var>. For example, for a probability plot of the uniform
distribution on [2,4] and <var>x</var>, use
<pre class="example"> ppplot (x, "uniform", 2, 4)
</pre>
<p class="noindent"><var>dist</var> can be any string for which a function <var>dist_cdf</var>
that calculates the CDF of distribution <var>dist</var> exists.
<p>If no output arguments are given, the data are plotted directly.
</p></blockquote></div>
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