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  2. Probability mass function - Wikipedia

    en.wikipedia.org/wiki/Probability_mass_function

    The graph of a probability mass function. All the values of this function must be non-negative and sum up to 1. In probability and statistics, a probability mass function (sometimes called probability function or frequency function [1]) is a function that gives the probability that a discrete random variable is exactly equal to some value. [2]

  3. Convolution of probability distributions - Wikipedia

    en.wikipedia.org/wiki/Convolution_of_probability...

    The probability distribution of the sum of two or more independent random variables is the convolution of their individual distributions. The term is motivated by the fact that the probability mass function or probability density function of a sum of independent random variables is the convolution of their corresponding probability mass functions or probability density functions respectively.

  4. Joint probability distribution - Wikipedia

    en.wikipedia.org/wiki/Joint_probability_distribution

    In probability theory, the joint probability distribution is the probability distribution of all possible pairs of outputs of two random variables that are defined on the same probability space. The joint distribution can just as well be considered for any given number of random variables.

  5. Probability distribution - Wikipedia

    en.wikipedia.org/wiki/Probability_distribution

    In the discrete case, it is sufficient to specify a probability mass function assigning a probability to each possible outcome (e.g. when throwing a fair die, each of the six digits “1” to “6”, corresponding to the number of dots on the die, has the probability ).

  6. Geometric distribution - Wikipedia

    en.wikipedia.org/wiki/Geometric_distribution

    An alternative parameterization of the distribution gives the probability mass function (=) = () where = and =. [ 1 ] : 208–209 An example of a geometric distribution arises from rolling a six-sided die until a "1" appears.

  7. Discrete uniform distribution - Wikipedia

    en.wikipedia.org/wiki/Discrete_uniform_distribution

    In probability theory and statistics, the discrete uniform distribution is a symmetric probability distribution wherein each of some finite whole number n of outcome values are equally likely to be observed. Thus every one of the n outcome values has equal probability 1/n. Intuitively, a discrete uniform distribution is "a known, finite number ...

  8. Poisson binomial distribution - Wikipedia

    en.wikipedia.org/wiki/Poisson_binomial_distribution

    1.1 Probability Mass Function. 1.2 Cumulative distribution function. 2 Properties. ... poibin - Python implementation - can compute the PMF and CDF, ...

  9. Multinomial distribution - Wikipedia

    en.wikipedia.org/wiki/Multinomial_distribution

    The probability mass function can be expressed using the gamma function as: (, ...