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Concept
Randomization
Résumé
Randomization is the process of making something random. Randomization is not haphazard; instead, a random process is a sequence of random variables describing a process whose outcomes do not follow a deterministic pattern, but follow an evolution described by probability distributions. For example, a random sample of individuals from a population refers to a sample where every individual has a known probability of being sampled. This would be contrasted with nonprobability sampling where arbitrary individuals are selected.
In various contexts, randomization may involve:
generating a random permutation of a sequence (such as when shuffling cards);
selecting a random sample of a population (important in statistical sampling);
allocating experimental units via random assignment to a treatment or control condition;
generating random numbers (random number generation); or
transforming a data stream (such as when using a scrambler in telecommunications).
Applications of randomness
Randomization is used in statistics and in gambling.
Randomization is a core principle in statistical theory, whose importance was emphasized by Charles S. Peirce in "Illustrations of the Logic of Science" (1877–1878) and "A Theory of Probable Inference" (1883). Randomization-based inference is especially important in experimental design and in survey sampling. The first use of "randomization" listed in the Oxford English Dictionary is its use by Ronald Fisher in 1926.
Randomized experiment
Randomized controlled trial
In the statistical theory of design of experiments, randomization involves randomly allocating the experimental units across the treatment groups. For example, if an experiment compares a new drug against a standard drug, then the patients should be allocated to either the new drug or to the standard drug control using randomization. Randomization reduces confounding by equalising so-called factors ( independent variables) that have not been accounted for in the experimental design.
Source officielle
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