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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. This means that the particular outcome sequence will contain some patterns detectable in hindsight but impossible to foresee.
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.
A hardware random number generator is expected to output near-perfect random numbers ("full entropy"). [1] A physical process usually does not have this property, and a practical TRNG typically includes a few blocks: [9] a noise source that implements the physical process producing the entropy. Usually this process is analog, so a digitizer is ...
Random. On Wikipedia and other sites running on MediaWiki, Special:Random can be used to access a random article in the main namespace; this feature is useful as a tool to generate a random article. Depending on your browser, it's also possible to load a random page using a keyboard shortcut (in Firefox, Edge, and Chrome Alt-Shift + X ).
Randomness test. A randomness test (or test for randomness ), in data evaluation, is a test used to analyze the distribution of a set of data to see whether it can be described as random (patternless). In stochastic modeling, as in some computer simulations, the hoped-for randomness of potential input data can be verified, by a formal test for ...
A pseudorandom number generator ( PRNG ), also known as a deterministic random bit generator ( DRBG ), [1] is an algorithm for generating a sequence of numbers whose properties approximate the properties of sequences of random numbers. The PRNG-generated sequence is not truly random, because it is completely determined by an initial value ...
The Lehmer random number generator [1] (named after D. H. Lehmer ), sometimes also referred to as the Park–Miller random number generator (after Stephen K. Park and Keith W. Miller), is a type of linear congruential generator (LCG) that operates in multiplicative group of integers modulo n. The general formula is.
A random variable is the simplest type of random element. It is a map is a measurable function from the set of possible outcomes to . As a real-valued function, often describes some numerical quantity of a given event. E.g. the number of heads after a certain number of coin flips; the heights of different people.