Random number

Short description: 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.

## Contents

* 1 Algorithms and implementations
* 2 Common understanding
* 3 Real world consequences
* 4 See also
* 5 References

## Algorithms and implementations

Random numbers are frequently used in algorithms such as Knuth's 1964-developed algorithm[1] for shuffling lists. (popularly known as the Knuth shuffle or the Fisher–Yates shuffle, based on work they did in 1938).

In 1999, a new feature was added to the Pentium III: a hardware-based random number generator.[2][3] It has been described as "several oscillators combine their outputs and that odd waveform is sampled asynchronously."[4] These numbers, however, were only 32 bit, at a time when export controls were on 56 bits and higher, so they were not state of the art.[5]

## 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."[6]

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.[7][8][example needed]

## Real world consequences

Flaws in randomness have real-world consequences.[9][10]

A 99.8% randomness was shown by researchers to negatively affect an estimated 27,000 customers of a large service[9] and that the problem was not limited to just that situation.[clarification needed]

## See also

* Algorithmically random sequence
* Quasi-random sequence
* Random number generation
* Random sequence
* Random variable
* Random variate
* Random real

## References

1. ↑ Richard Durstenfeld (July 1964). "Algorithm 235: Random permutation". Communications of the ACM 7 (7): 420. doi:10.1145/364520.364540.
2. ↑ Robert Moscowitz (July 12, 1999). "Privacy's Random Nature". Network Computing.
3. ↑ "Hardwiring Security". Wired. January 1999. https://www.wired.com/1999/01/hardwiring-security.
4. ↑ Terry Ritter (January 21, 1999). "The Pentium III RNG". http://www.ciphersbyritter.com/NEWS4/PENTRAND.HTM.
5. ↑ "Unpredictable Randomness Definition". https://www.irisa.fr/caps/projects/hipsor/misc.php.
6. ↑ Jonathan Knudson (January 1998). "Javatalk: Horseshoes, hand grenades and random numbers". Sun Server: 16–17.
7. ↑ Tom Hays (April 16, 1995). "NYPD Bad Cop's Illegal Search Mars Career". Los Angeles Times. https://www.latimes.com/archives/la-xpm-1995-04-16-mn-55166-story.html.
8. ↑ A pre-compiled list of apartment numbers would be a violation thereof.
9. ↑ 9.0 9.1 John Markoff (February 14, 2012). "Flaw Found in an Online Encryption Method". New York Times. https://www.nytimes.com/2012/02/15/technology/researchers-find-flaw-in-an-online-encryption-method.html.
10. ↑ Reid Forgrave (May 3, 2018). "The man who cracked the lottery". New York Times. https://www.nytimes.com/interactive/2018/05/03/magazine/money-issue-iowa-lottery-fraud-mystery.html.

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