Random number generator

⚠️ Warning: This is a draft ⚠️

This means it might contain formatting issues, incorrect code, conceptual problems, or other severe issues.

If you want to help to improve and eventually enable this page, please fork RosettaGit's repository and open a merge request on GitHub.

A '''random number generator''' picks numbers at chance from a distribution.

The most common type is a ''uniform generator'', where each number has an equal chance. If a uniform generator yields decimal digits from 0 to 9, then each digit has a 10% chance. The other type is a [[unbias a random generator|''weighted'' or ''biased'' generator]], where the chances are not equal. A biased generator that yields 0 with 70% chance, yields 1 with 30% chance, would probably yield more zeros than ones.

''True random numbers'' are impossible to predict. Many programs use ''pseudorandom numbers'', which are not as good. A pseudorandom generator uses a formula and a state to calculate a sequence of numbers. Anyone who knows the formula and the state can predict those numbers.

Pseudorandom numbers can also have statistical problems. True random numbers are [[wp:independence (probability theory)|independent]]. A pseudorandom sequence may contain patterns where the values of some numbers change the probabilities of other numbers.