Continuous probability distribution/Related Articles: Difference between revisions
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Revision as of 14:40, 11 January 2010
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- Discrete probability distribution [r]: Class of probability distributions in which the values that might be observed are restricted to being within a pre-defined list of possible values. [e]
- Entropy of a probability distribution [r]: A number that describes the degree of uncertainty or disorder the distribution represents. [e]
- Exponential distribution [r]: Class of continuous probability distributions that describe the times between events in a Poisson process, i.e. a process in which events occur continuously and independently at a constant average rate. [e]
- Measure theory [r]: Generalization of the concepts of length, area, and volume, to arbitrary sets of points not composed of line segments or rectangles. [e]
- Normal distribution [r]: a symmetrical bell-shaped probability distribution representing the frequency of random variations of a quantity from its mean. [e]
- Poisson distribution [r]: a probability distribution that is typically used to model the number of independent events (occurring at a constant average rate) that fall within a stated interval. [e]
- Probability distribution [r]: Function of a discrete random variable yielding the probability that the variable will have a given value. [e]
- Sigma algebra [r]: A formal mathematical structure intended among other things to provide a rigid basis for measure theory and axiomatic probability theory. [e]