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Random sequence. The concept of a random sequence is essential in probability theory and statistics. The concept generally relies on the notion of a sequence of random variables and many statistical discussions begin with the words "let X1,..., Xn be independent random variables...". Yet as D. H. Lehmer stated in 1951: "A random sequence is a ...
Algorithmically random sequence. Intuitively, an algorithmically random sequence (or random sequence) is a sequence of binary digits that appears random to any algorithm running on a (prefix-free or not) universal Turing machine. The notion can be applied analogously to sequences on any finite alphabet (e.g. decimal digits).
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.
[58] [59] If the index set is the integers, or some subset of them, then the stochastic process can also be called a random sequence. [ 55 ] If the state space is the integers or natural numbers, then the stochastic process is called a discrete or integer-valued stochastic process .
Definition. A sequence of real-valued random variables, with cumulative distribution functions , is said to converge in distribution, or converge weakly, or converge in law to a random variable X with cumulative distribution function F if. for every number at which is continuous.
Probability theory. In probability and statistics, a Bernoulli process (named after Jacob Bernoulli) is a finite or infinite sequence of binary random variables, so it is a discrete-time stochastic process that takes only two values, canonically 0 and 1. The component Bernoulli variables Xi are identically distributed and independent.
Pseudorandom number generator. 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 ...
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 ...