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  2. Random number - Wikipedia

    en.wikipedia.org/wiki/Random_number

    When a cubical die is rolled, a random number from 1 to 6 is obtained. A random number is generated by a random process such as throwing Dice. Individual numbers can't be predicted, but the likely result of generating a large quantity of numbers can be predicted by specific mathematical series and statistics.

  3. Random number generation - Wikipedia

    en.wikipedia.org/wiki/Random_number_generation

    Dice are an example of a 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 is generated that cannot be reasonably predicted better than by random chance.

  4. List of probability distributions - Wikipedia

    en.wikipedia.org/wiki/List_of_probability...

    The Rademacher distribution, which takes value 1 with probability 1/2 and value −1 with probability 1/2. The binomial distribution, which describes the number of successes in a series of independent Yes/No experiments all with the same probability of success.

  5. Template:Random number - Wikipedia

    en.wikipedia.org/wiki/Template:Random_number

    Varying prime (provided that they are odd prime numbers) generates pseudo-random that have independent random distribution. Note that when count is even (such as 100 by default, or 1000 in the examples above), the generated numbers (on the same page) are all odd or all even when you are varying the seed or prime , unless half of the calls use ...

  6. List of random number generators - Wikipedia

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

    A class of chaotic counter-based generators applying a broad class of non-invertible generalized Collatz mappings and Weyl sequences, enabling the generation of multiple independent streams. Leveraging 128-bit arithmetic allows for a highly efficient implementation, especially on modern 64-bit architectures.

  7. 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.

  8. Sampling (statistics) - Wikipedia

    en.wikipedia.org/wiki/Sampling_(statistics)

    To do this, we could allocate the first school numbers 1 to 150, the second school 151 to 330 (= 150 + 180), the third school 331 to 530, and so on to the last school (1011 to 1500). We then generate a random start between 1 and 500 (equal to 1500/3) and count through the school populations by multiples of 500.

  9. A Million Random Digits with 100,000 Normal Deviates

    en.wikipedia.org/wiki/A_Million_Random_Digits...

    A Million Random Digits with 100,000 Normal Deviates is a random number book by the RAND Corporation, originally published in 1955. The book, consisting primarily of a random number table , was an important 20th century work in the field of statistics and random numbers .

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