# Documentation

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# Uniform Distribution (Continuous)

Evaluate and generate random samples from continuous uniform distribution

## Functions

 `makedist` Create probability distribution object
 `cdf` Cumulative distribution functions `icdf` Inverse cumulative distribution functions `iqr` Interquartile range `mean` Mean of probability distribution `median` Median of probability distribution `pdf` Probability density functions `random` Random numbers `std` Standard deviation of probability distribution `truncate` Truncate probability distribution object `var` Variance of probability distribution
 `unifcdf` Continuous uniform cumulative distribution function `unifpdf` Continuous uniform probability density function `unifinv` Continuous uniform inverse cumulative distribution function `unifit` Continuous uniform parameter estimates `unifstat` Continuous uniform mean and variance `unifrnd` Continuous uniform random numbers

## Using Objects

 `UniformDistribution` Uniform probability distribution object

## Examples and How To

Generate Random Numbers Using Uniform Distribution Inversion

This example shows how to generate random numbers using the uniform distribution inversion method.

## Concepts

Uniform Distribution (Continuous)

The uniform distribution (also called the rectangular distribution) is notable because it has a constant probability distribution function between its two bounding parameters.