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  2. Random number generation - Wikipedia

    en.wikipedia.org/wiki/Random_number_generation

    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. Random number generation is a process by which, often by means of a random number generator (RNG), a sequence of numbers or symbols that cannot be reasonably predicted better than by random chance is generated.

  3. List of random number generators - Wikipedia

    en.wikipedia.org/wiki/List_of_random_number...

    However, generally they are considerably slower (typically by a factor 2–10) than fast, non-cryptographic random number generators. These include: Stream ciphers. Popular choices are Salsa20 or ChaCha (often with the number of rounds reduced to 8 for speed), ISAAC, HC-128 and RC4. Block ciphers in counter mode.

  4. Random number table - Wikipedia

    en.wikipedia.org/wiki/Random_number_table

    Random number tables have been used in statistics for tasks such as selected random samples. This was much more effective than manually selecting the random samples (with dice, cards, etc.). Nowadays, tables of random numbers have been replaced by computational random number generators. If carefully prepared, the filtering and testing processes ...

  5. Mersenne Twister - Wikipedia

    en.wikipedia.org/wiki/Mersenne_Twister

    The Mersenne Twister is a general-purpose pseudorandom number generator (PRNG) developed in 1997 by Makoto Matsumoto (松本 眞) and Takuji Nishimura (西村 拓士). [1][2] Its name derives from the choice of a Mersenne prime as its period length. The Mersenne Twister was designed specifically to rectify most of the flaws found in older PRNGs.

  6. Monte Carlo method - Wikipedia

    en.wikipedia.org/wiki/Monte_Carlo_method

    the (pseudo-random) number generator has certain characteristics (e.g. a long "period" before the sequence repeats) the (pseudo-random) number generator produces values that pass tests for randomness; there are enough samples to ensure accurate results; the proper sampling technique is used; the algorithm used is valid for what is being modeled

  7. Random number - Wikipedia

    en.wikipedia.org/wiki/Random_number

    Random number. 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 can't be predicted, but the likely result of generating a large quantity of numbers ...

  8. Randomness - Wikipedia

    en.wikipedia.org/wiki/Randomness

    In common usage, randomness is the apparent or actual lack of definite pattern or predictability in information. [1][2] A random sequence of events, symbols or steps often has no order and does not follow an intelligible pattern or combination. Individual random events are, by definition, unpredictable, but if there is a known probability ...

  9. Fisher–Yates shuffle - Wikipedia

    en.wikipedia.org/wiki/Fisher–Yates_shuffle

    Fisher–Yates shuffle. The Fisher–Yates shuffle is an algorithm for shuffling a finite sequence. The algorithm takes a list of all the elements of the sequence, and continually determines the next element in the shuffled sequence by randomly drawing an element from the list until no elements remain. [1] The algorithm produces an unbiased ...