Statistical Visualization
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 ▪ ...
Model Fitting
ListFitPlot — plot data with fitted curves
ListFitPlot3D — plot data with fitted surfaces
Charting »
BarChart ▪ 
PieChart ▪ 
BubbleChart ▪ ...
Data Visualization »
ListPlot ▪ 
ListPlot3D ▪ 
ListContourPlot ▪ ...
Date & Time Visualization »
DateListPlot ▪ 
TimelinePlot ▪ 
DateHistogram ▪ ...
Function Visualization »
Plot ▪ 
Plot3D ▪ 
DiscretePlot ▪ 
DiscretePlot3D ▪ 
ContourPlot ▪ ...
Wolfram Community: Statistics and Probability