Difference between revisions of "Probability distribution"
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Latest revision as of 17:59, 4 April 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
- Probability distribution @ Wikipedia
