Lamun ''u'' ngarupakeun nilai sampel tina standar sebaran seragam , mangka nilai ''a'' + (''b'' - ''a'')''u'' nuturkeun sebaran seragam nu di-parameterisasi ku ''a'' jeung ''b'', saperti nu dijelaskeun di luhur. Transpromasi sejenna bisa digunakeun keur nyaruakeun sebaran statistik sejenna tina sebaran seragam (tempo ''pamakean'' di handap)
Uses of the uniform distribution ===
In [[ statistics]], when a [[p-value]] is used as a test statistic for a simple [[null hypothesis]], and the distribution of the test statistic is continuous, then the test statistic is uniformly distributed between 0 and 1 if the null hypothesis is true.
Although the uniform distribution is not commonly found in nature, it is particularly useful for sampling from arbitrary distributions.
A general method is the [[inverse transform sampling method]], which uses the [[cumulative distribution function]] (CDF) of the target random variable. This method is very useful in theoretical work. Since simulations using this method require inverting the CDF of the target variable, alternative methods have been divised for the cases where the CDF is not known in closed form. One such method is [[rejection sampling]].
The [[normal distribution]] is an important example where the inverse transform method is not efficient. However, there is an exact method, the [[Box-Muller transformation]], which uses the inverse transform to convert two independent uniform [[random variable]] s into two independent [[ normal distribution|normally distributed]] random variables.