Randomization Technique

Computer algorithms are deterministic and can't actually produce random numbers. In place of truly random numbers, pseudo-random number generators produce numbers in a way that cannot predicted and are statistically similar to truly random numbers.
  1. Seeding

    • Most pseudo-random number generators use recursion functions that need an initial value, or seed, to get started. The least significant digit on a computer's clock, the thousandth of a second place for example, is often used to seed the algorithm since the user won't know the value of the seed.

    Tests

    • Series of numbers produced by pseudo-random number generators are tested statistically to ensure they have the same properties, such as average and distribution, over the same range.

    Physical Devices

    • In principle, a physical device, for instance one that measures atomic decay, could be used to produce random numbers. But since the numbers produced by these devices are not provably random, their outputs must be tested just like the outputs of pseudo-random number generators.

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