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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 datai against the CDF of a reference distribution ref.

Details and Options
Details and Options Details and Options
Examples  
Basic Examples  
Scope  
Data and Distributions  
Tabular Data  
Presentation  
Options  
ColorFunction  
ColorFunctionScaling  
Filling  
Show More Show More
FillingStyle  
Joined  
Mesh  
MeshFunctions  
MeshShading  
MeshStyle  
PlotHighlighting  
PlotLegends  
PlotMarkers  
PlotStyle  
PlotTheme  
ReferenceLineStyle  
ScalingFunctions  
Applications  
Properties & Relations  
See Also
Related Guides
History
Cite this Page

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 datai against the CDF of a reference distribution ref.

Details and Options

Examples

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Basic Examples  (4)

A normal probability plot compared to an estimated normal distribution:

Compare to the standard normal distribution:

A probability-probability plot of two datasets:

Plot several datasets with a legend:

Scope  (26)

Data and Distributions  (12)

ProbabilityPlot works with numeric data:

ProbabilityPlot works with symbolic distributions:

Use multiple datasets and distributions:

The default reference distribution is the closest estimated NormalDistribution :

Specify data or distributions as the reference:

Reference distributions are estimated for each dataset:

Estimate specific reference distributions for numeric datasets:

Use all forms of built-in distributions:

Parametric:

Nonparametric:

Derived:

Plot values with units:

Plot the values from an association:

Plot data with weights:

Plot data from time series:

Tabular Data  (1)

Get tabular data:

Compare the data to a normal distribution:

Compare multiple sets of data:

Use PivotToColumns to generate columns of "SepalWidth" per species:

Compare probability of sepal width per species:

Use abbreviated names for extended keys when the elements are unique:

Use legends for the plot:

Presentation  (13)

Multiple datasets are automatically colored to be distinct:

Provide explicit styling to different sets:

Include legends for each dataset:

Add labels:

Use specific styles for the reference line:

Turn off the reference line:

Provide an interactive Tooltip for the data:

Provide a specific tooltip for the data:

Create filled plots:

Use shapes to distinguish different datasets:

Use Joined to connect datasets with lines:

Use a theme with grid lines:

Data usually has interactive callouts showing the coordinates when you mouse over them:

Including specific wrappers or interactions such as tooltips turns off the interactive features:

Choose from multiple interactive highlighting effects:

Options  (67)

ColorFunction  (6)

ColorFunction requires at least one dataset to be Joined :

Color by scaled and coordinates:

Color with a named color scheme:

Fill to the reference line with the color used for the curve:

ColorFunction has higher priority than PlotStyle for coloring the curve:

Use Automatic in MeshShading to use ColorFunction :

ColorFunctionScaling  (2)

Color the line based on scaled value:

Color the line based on unscaled value:

Filling  (6)

Fill from the data to the reference line:

Use symbolic or explicit values for filling:

Points fill with stems:

Curves fill with solid regions:

Fill from the third dataset to the axis:

Fill between datasets using a particular style:

Use different styles above and below the filling level:

FillingStyle  (2)

Use different fill colors:

Use a transparent orange filling:

Joined  (2)

Datasets are not joined by default:

Join the points:

Symbolic distributions are joined by default:

Mesh  (3)

Use 20 mesh levels evenly spaced in the direction:

Use the mesh to divide the curve into deciles:

Specify Style and mesh levels in the direction:

MeshFunctions  (2)

Use a mesh evenly spaced in the and directions:

Show 5 mesh levels in the direction (red) and 10 in the direction (blue):

MeshShading  (6)

Alternate red and blue segments of equal width in the direction:

Use None to remove segments:

MeshShading can be used with PlotStyle :

MeshShading has higher priority than PlotStyle for styling the curve:

Use PlotStyle for some segments by setting MeshShading to Automatic :

MeshShading can be used with ColorFunction :

MeshStyle  (4)

Color the mesh the same color as the plot:

Use a red mesh in the direction:

Use a red mesh in the direction and a blue mesh in the direction:

Use big red mesh points in the direction:

PlotHighlighting  (8)

Plots have interactive coordinate callouts with the default setting PlotHighlighting Automatic :

Use PlotHighlighting None to disable the highlighting for the entire plot:

Move the mouse over the curve to highlight it with a ball and label:

Move the mouse over the curve to highlight it with a label and droplines to the axes:

Move the mouse over the plot to highlight it with a slice showing values corresponding to the position:

Move the mouse over the plot to highlight it with a slice showing values corresponding to the position:

Use a component that shows the points on the dataset closest to the position of the mouse cursor:

Specify the style for the points:

Use a component that shows the coordinates on the dataset closest to the mouse cursor:

Use Callout options to change the appearance of the label:

Combine components to create a custom effect:

PlotLegends  (7)

By default, no legends are used:

Generate a legend using labels:

Generate a legend using placeholders:

Legends use the same styles as the plot:

Use Placed to specify the legend placement:

Place the legend inside the plot:

Use LineLegend to change the legend appearance:

PlotMarkers  (7)

ProbabilityPlot normally uses distinct colors to distinguish different sets of data:

Automatically use colors and shapes to distinguish sets of data:

Use shapes only:

Change the size of the default plot markers:

Use arbitrary text for plot markers:

Use explicit graphics for plot markers:

Use the same symbol for all the sets of data:

PlotStyle  (3)

Use different style directives:

By default, different styles are chosen for multiple curves:

Explicitly specify the style for different curves:

PlotTheme  (2)

Use a theme with grid lines:

Use a theme with high-contrast colors:

Turn off the grid lines:

ReferenceLineStyle  (4)

ReferenceLineStyle by default uses a Dotted form of PlotStyle :

Draw a dotted red reference line:

Draw a solid red reference line:

Use None to turn off the reference line:

ReferenceLineStyle can be combined with PlotStyle :

ScalingFunctions  (2)

Data is normally shown on linear scales:

Plot the data on a log-scaled axis:

Applications  (3)

KolmogorovSmirnovTest can be used to create a measure that quantifies the behavior in ProbabilityPlot . The KolmogorovSmirnov test statistic is equivalent to the maximum vertical distance between a point in the plot and the reference line:

The -value is larger when the points are closer to the reference line:

A -test for location assumes that the data was drawn from a NormalDistribution . If this assumption does not hold, a nonparametric test such as a signed-rank test is more appropriate. Suppose one wants to test for a location parameter of zero using the following data:

The plot suggests that the tails of the distribution are quite heavy. A SignedRankTest for location is more appropriate than the TTest :

Compare two time slices for a random process:

Properties & Relations  (8)

With no second argument, data is compared against an estimated normal distribution:

QuantilePlot compares quantiles for the data:

ProbabilityScalePlot scales the axes so that points from distributions are on a straight line:

BoxWhiskerChart and DistributionChart can be used to visualize the distribution of data:

SmoothHistogram and Histogram can be used to visualize the distribution of data:

DiscretePlot can be used to visualize the discrete distributions:

Use ListPlot to see the data:

ProbabilityPlot ignores time stamps when input is a TimeSeries :

Wolfram Research (2010), ProbabilityPlot, Wolfram Language function, https://reference.wolfram.com/language/ref/ProbabilityPlot.html (updated 2025).

Text

Wolfram Research (2010), ProbabilityPlot, Wolfram Language function, https://reference.wolfram.com/language/ref/ProbabilityPlot.html (updated 2025).

CMS

Wolfram Language. 2010. "ProbabilityPlot." Wolfram Language & System Documentation Center. Wolfram Research. Last Modified 2025. https://reference.wolfram.com/language/ref/ProbabilityPlot.html.

APA

Wolfram Language. (2010). ProbabilityPlot. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/ProbabilityPlot.html

BibTeX

@misc{reference.wolfram_2025_probabilityplot, author="Wolfram Research", title="{ProbabilityPlot}", year="2025", howpublished="\url{https://reference.wolfram.com/language/ref/ProbabilityPlot.html}", note=[Accessed: 05-December-2025]}

BibLaTeX

@online{reference.wolfram_2025_probabilityplot, organization={Wolfram Research}, title={ProbabilityPlot}, year={2025}, url={https://reference.wolfram.com/language/ref/ProbabilityPlot.html}, note=[Accessed: 05-December-2025]}

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