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Random number

Number generated by a random process

Random number
Summary

Number generated by a random process

[[Dice]] are an example of a mechanical hardware random number generator. When a cubical die is rolled, a random number from 1 to 6 is obtained.

A random number is generated by a random (stochastic) process such as throwing dice. Individual numbers cannot be predicted, but the likely result of generating a large quantity of numbers can be predicted by specific mathematical series and statistics.

Algorithms and implementations

Random numbers are frequently used in algorithms such as Knuth's 1964-developed algorithm{{cite journal |author=Richard Durstenfeld

In 1999, a new feature was added to the Pentium III: a hardware-based random number generator.

Common understanding

In common understanding, "1 2 3 4 5" is not as random as "3 5 2 1 4" and certainly not as random as "47 88 1 32 41" but "we can't say authoritavely that the first sequence is not random ... it could have been generated by chance."

When a police officer claims to have done a "random .. door-to-door" search, there is a certain expectation that members of a jury will have.

Real world consequences

Flaws in randomness have real-world consequences.{{cite news

A 99.8% randomness was shown by researchers to negatively affect an estimated 27,000 customers of a large service and that the problem was not limited to just that situation.

References

References

  1. A pre-compiled list of apartment numbers would be a violation thereof.
Wikipedia Source

This article was imported from Wikipedia and is available under the Creative Commons Attribution-ShareAlike 4.0 License. Content has been adapted to SurfDoc format. Original contributors can be found on the article history page.

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