Random number
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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[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]Template:Examples
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.Template:Clarify
See also
- Algorithmically random sequence
- Quasi-random sequence
- Random number generation
- Random sequence
- Random variable
- Random variate
- Random real
References
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- ↑ A pre-compiled list of apartment numbers would be a violation thereof.
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