Using Probability Distributions

Probability distributions are theoretical distributions based on assumptions about a source population. They assign probability to the event that a random variable takes on a specific, discrete value, or falls within a specified range of continuous values. There are two main types of models:

• Parametric Models—Choose a model based on a parametric family of probability distributions and then adjust the parameters to fit the data. For information on supported parametric distributions, see Parametric Distributions.

• Nonparametric Models—When data or statistics do not follow any standard probability distribution, nonparametric models may be appropriate. For information on supported nonparametric distributions, see Nonparametric Distributions.

The Statistics Toolbox provides several ways of working with both parametric and nonparametric probability distributions:

• Graphic User Interfaces (GUIs)—Interact with the distributions to visualize distributions, fit a distribution to your data, or generate random data using a specific distribution. For more information, see Working with Distributions Through GUIs.

• Command Line Functions—Use command-line functions to further explore the distributions, fit relevant models to your data, or generate random data. For more information on using functions, see Statistics Toolbox Distribution Functions.

• Distribution Objects—Use objects to explore and fit your data to a distribution, save the results to a single entity, and generate random data from the resulting parameters. For more information, see Using Probability Distribution Objects.

Probability Distributions

Supported Distributions

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