Statistical visualization is used to understand how data is distributed and how that compares to other datasets and distributions. Histograms and smooth histograms both effectively estimate the various distribution functions, either through binning or smoothing. Quantile and related plots compare data to a reference distribution. Box-and-whisker and distribution charts compare a number of data distributions to each other. All the statistical visualization functions provide high levels of automation of aesthetics and statistical computations including automatic bin selection, bandwidth determination, and distribution parameter estimation. All functions also give detailed access to customize both aesthetics and statistical computations.

Distribution Shapes

Histogram — plot a histogram of data

SmoothHistogram — plot a density estimate of data

Histogram3D   ▪ SmoothHistogram3D   ▪ DensityHistogram
SmoothDensityHistogram   ▪ PairedHistogram   ▪ PairedSmoothHistogram

BarSpacing   ▪ BarOrigin   ▪ GridLines   ▪ ScalingFunctions   ▪ ...

Distribution Fits

QuantilePlot — quantile-quantile plot of data or distributions

ProbabilityPlot — probability-probability plot of data or distributions

ProbabilityScalePlot — normal plot, Weibull plot, Gumbel plot, etc.

ReferenceLineStyle   ▪ ScalingFunctions   ▪ GridLines   ▪ ...

Distribution Comparisons

BoxWhiskerChart — box-and-whisker chart of multiple datasets

DistributionChart — distribution chart of multiple datasets

BarSpacing   ▪ BarOrigin   ▪ ChartElementFunction   ▪ ScalingFunctions   ▪ ...

Charting »

BarChart   ▪ PieChart   ▪ BubbleChart   ▪ ...

Data Visualization »

ListPlot   ▪ ListPlot3D   ▪ ListContourPlot   ▪ ...

Date & Time Visualization »

DateListPlot   ▪ TimelinePlot   ▪ DateHistogram   ▪ ...

Function Visualization »

Plot   ▪ Plot3D   ▪ DiscretePlot   ▪ DiscretePlot3D   ▪ ContourPlot   ▪ ...

Geographic Visualization »

GeoListPlot   ▪ GeoHistogram   ▪ GeoSmoothHistogram   ▪ ...