BUILT-IN MATHEMATICA SYMBOL

# ProbabilityPlot

ProbabilityPlot[list]
generates a plot of the CDF of list against the CDF of a normal distribution.

ProbabilityPlot[dist]
generates a plot of the CDF of the distribution dist against the CDF of a normal distribution.

ProbabilityPlot[data, rdata]
generates a plot of the CDF of data against the CDF of rdata.

ProbabilityPlot[data, rdist]
generates a plot of the CDF of data against the CDF of symbolic distribution rdist.

ProbabilityPlot[{data1, data2, ...}, ref]
generates a plot of the CDF of against the CDF of a reference distribution ref.

## Details and OptionsDetails and Options

• ProbabilityPlot[data1, data2] works with being either a dataset of real values or a symbolic univariate distribution.
• For datasets list, empirical CDFs are used, and for symbolic distributions dist, exact CDFs are used.
• ProbabilityPlot[data, dist[1, ...]] with symbolic parameters is equivalent to ProbabilityPlot[data, EstimatedDistribution[data, dist[1, ...]]].
• The form or provides a wrapper w to be applied to the resulting graphics primitives.
• The following wrappers can be used:
•  Annotation[e,label] provide an annotation Button[e,action] define an action to execute when the element is clicked EventHandler[e,...] define a general event handler for the element Hyperlink[e,uri] make the element act as a hyperlink PopupWindow[e,cont] attach a popup window to the element StatusArea[e,label] display in the status area when the element is moused over Style[e,opts] show the element using the specified styles Tooltip[e,label] attach an arbitrary tooltip to the element
• ProbabilityPlot has the same options as Graphics, with the following additions and changes:
•  AspectRatio 1/GoldenRatio ratio of width to height ClippingStyle Automatic what to draw where curves are clipped ColorFunction Automatic how to determine the coloring of curves ColorFunctionScaling True whether to scale arguments to ColorFunction Filling None filling to insert under each curve FillingStyle Automatic style to use for filling Joined Automatic whether to join points Mesh None how many mesh points to draw on each curve MeshFunctions {#1&} how to determine the placement of mesh points MeshShading None how to shade regions between mesh points MeshStyle Automatic the style for mesh points Method Automatic methods to use PerformanceGoal \$PerformanceGoal aspects of performance to try to optimize PlotLegends None legends for data points PlotMarkers None markers to use to indicate each point for datasets PlotRange Automatic range of values to include PlotRangeClipping True whether to clip at the plot range PlotStyle Automatic graphics directives to specify the style for each object ReferenceLineStyle Automatic style for the reference line ScalingFunctions None how to scale individual coordinates WorkingPrecision MachinePrecision the precision used in internal computations for symbolic distributions
• With , the region between a dataset and reference line will be filled. By default, "stems" are used for datasets, and "solid" filling is used for symbolic distributions. The setting will force "solid" filling for datasets.
• The arguments supplied to functions in MeshFunctions and RegionFunction are , . Functions in ColorFunction are by default supplied with scaled versions of these arguments.
• The setting is equivalent to when comparing two distributions and otherwise.
• The setting uses a sequence of different plot styles for different lines.
• With the , no reference line will be drawn.
• Typical settings for PlotLegends include:
•  None no legend Automatic automatically determine legend {lbl1,lbl2,...} use , , ... as legend labels Placed[lspec,...] specify placement for legend
• With ScalingFunctions->{sx, sy}, the coordinate is scaled using and the coordinate is scaled using .

## ExamplesExamplesopen allclose all

### Basic Examples (4)Basic Examples (4)

A normal probability plot compared to an estimated normal distribution:

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Compare to the standard normal distribution:

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A probability-probability plot of two datasets:

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Plot several datasets with a legend:

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## See AlsoSee Also

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