Random number
In mathematics and statistics, a random number is either Pseudo-random or a number generated for, or part of, a set exhibiting statistical randomness.
Algorithms and implementations
A 1964-developed algorithm[1] is popularly known as the Knuth shuffle or the Fisher–Yates shuffle (based on work they did in 1938). A real-world use for this is sampling water quality in a reservoir.
In 1999, a new feature was added to the
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.
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
- .
- ^ Robert Moscowitz (July 12, 1999). "Privacy's Random Nature". Network Computing.
- ^ "Hardwiring Security". Wired. January 1999.
- ^ Terry Ritter (January 21, 1999). "The Pentium III RNG".
- ^ "Unpredictable Randomness Definition". IRISA.
- ^ Jonathan Knudson (January 1998). "Javatalk: Horseshoes, hand grenades and random numbers". Sun Server. pp. 16–17.
- ^ Tom Hays (April 16, 1995). "NYPD Bad Cop's Illegal Search Mars Career". Los Angeles Times.
- ^ A pre-compiled list of apartment numbers would be a violation thereof.
- ^ New York Times.
- New York Times.