Probability Distributions

Data frequency models, random sample generation, parameter estimation

Fit probability distributions to sample data, evaluate probability functions such as pdf and cdf, calculate summary statistics such as mean and median, visualize sample data, generate random numbers, and so on. Work with probability distributions using probability distribution objects, command line functions, or interactive apps. For more information about each of these options, see Working with Probability Distributions.

Probability Distribution Basics

Click to go to the example, Compare Multiple Distribution Fits

Related Information

Descriptive Statistics and Probability Distributions (MathWorks Teaching Resources)

Featured Examples

Curve Fitting and Distribution Fitting

Perform curve fitting and distribution fitting, and learn when each method is appropriate.

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Simulating Dependent Random Variables Using Copulas

Use copulas to generate data from multivariate distributions when there are complicated relationships among the variables, or when the individual variables are from different distributions.

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Fitting a Univariate Distribution Using Cumulative Probabilities

Fit univariate distributions using least squares estimates of the cumulative distribution functions. This is a generally-applicable method that can be useful in cases when maximum likelihood fails, for instance some models that include a threshold parameter.