Difference between revisions of "Probability distribution"

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Revision as of 12:26, 2 March 2016

In probability and statistics, a probability distribution assigns a probability to each measurable subset of the possible outcomes of a random experiment, survey, or procedure of statistical inference.

Description

Examples are found in:

  • Experiments whose sample space is non-numerical, where the distribution would be a categorical distribution
  • Experiments whose sample space is encoded by discrete random variables, where the distribution can be specified by a probability mass function
  • Experiments with sample spaces encoded by continuous random variables, where the distribution can be specified by a probability density function

More complex experiments, such as those involving stochastic processes defined in continuous time, may demand the use of more general probability measures.

See also

External links