# Random number generation

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When a cubical die is rolled, a random number between 1 and 6 is obtained.

Random number generation is the generation of a sequence of numbers or symbols that cannot be reasonably predicted better than by a random chance, usually through a random-number generator (RNG).

Various applications of randomness have led to the development of several different methods for generating random data, of which some have existed since ancient times, among whose ranks are well-known “classic” examples, including the rolling of dice, coin flipping, the shuffling of playing cards, the use of yarrow stalks (for divination) in the I Ching, as well as countless other techniques. Because of the mechanical nature of these techniques, generating large numbers of sufficiently random numbers (important in statistics) required a lot of work and/or time. Thus, results would sometimes be collected and distributed as random number tables. Nowadays, after the advent of computational random-number generators, a growing number[quantify] of government-run lotteries and lottery games have started[when?] using RNGs instead of more traditional drawing methods. RNGs are also used to determine the outcomes of modern slot machines.[1]

Several computational methods for random-number generation exist. Many fall short of the goal of true randomness, although they may meet, with varying success, some of the statistical tests for randomness intended to measure how unpredictable their results are (that is, to what degree their patterns are discernible). However, carefully designed cryptographically secure computationally based methods of generating random numbers also exist, such as those based on the Yarrow algorithm, the Fortuna (PRNG), and others.

Contents

1 Practical applications and uses

2 “True” vs. pseudo-random numbers

3 Generation methods

3.1 Physical methods

3.2 Computational methods

3.3 Generation from a probability distribution

3.4 By humans

4 Post-processing and statistical checks

5 Other considerations

6 Low-discrepancy sequences as an alternative

7 Activities and demonstrations

8 Backdoors

9 In popular culture

10 See also

11 References

12 Further reading

13 External links

Practical applications and uses[edit]

Main articl

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