This is machine translation

Translated by Microsoft
Mouseover text to see original. Click the button below to return to the English version of the page.

Note: This page has been translated by MathWorks. Click here to see
To view all translated materials including this page, select Country from the country navigator on the bottom of this page.

Exploration and Visualization

Plot distribution functions, interactively fit distributions, create plots, and generate random numbers

Interactively fit probability distributions to sample data and export a probability distribution object to the MATLAB® workspace using the Distribution Fitter app. Explore the data range and identify potential outliers using box plots and quantile-quantile plots. Visualize the overall distribution by plotting a histogram with a fitted normal density function line. Assess whether your sample data comes from a population with a particular distribution, such as normal or Weibull, using probability plots. If a parametric distribution cannot adequately describe the sample data, compute and plot the empirical cumulative distribution function based on the sample data. Alternatively, estimate the cdf using a kernel smoothing function.


Distribution FitterFit probability distributions to data


expand all

boxplotBox plot
histfitHistogram with a distribution fit
normplotNormal probability plot
normspecNormal density plot shading between specifications
probplotProbability plots
qqplotQuantile-quantile plot
wblplotWeibull probability plot
cdfplotEmpirical cumulative distribution function (cdf) plot
ecdfEmpirical cumulative distribution function
ecdfhistHistogram based on empirical cumulative distribution function
ksdensityKernel smoothing function estimate for univariate and bivariate data
fsurfhtInteractive contour plot
Probability Distribution FunctionInteractive density and distribution plots
randtoolInteractive random number generation
surfhtInteractive contour plot


Model Data Using the Distribution Fitter App

The Distribution Fitter app provides a visual, interactive approach to fitting univariate distributions to data.

Fit a Distribution Using the Distribution Fitter App

Use the Distribution Fitter app to interactively fit a probability distribution to data.

Define Custom Distributions Using the Distribution Fitter App

Use the Distribution Fitter app to fit distributions not supported by the Statistics and Machine Learning Toolbox™ by defining a custom distribution.

Distribution Plots

Visually compare the empirical distribution of sample data with a specified distribution.

Nonparametric and Empirical Probability Distributions

Estimate a probability density function or a cumulative distribution function from sample data.

Grouping Variables

Grouping variables are utility variables used to group or categorize observations.