The functions described here are among the most commonly used discrete univariate statistical distributions. You can compute their densities, means, variances, and other ...

Different kinds of vector and matrix multiplication. This multiplies each element of the vector by the scalar k. The "dot" operator gives the scalar product of two vectors.

Exponential and related distributions occur in a variety of contexts, such as reliability and communication. As such, a large number of extensions and variations of ...

ChiSquareDistribution[\[Nu]] represents a \[Chi]^2 distribution with \[Nu] degrees of freedom.

LogNormalDistribution[\[Mu], \[Sigma]] represents a lognormal distribution derived from a normal distribution with mean \[Mu] and standard deviation \[Sigma].

BetaNegativeBinomialDistribution[\[Alpha], \[Beta], n] represents a beta negative binomial mixture distribution with beta distribution parameters \[Alpha] and \[Beta], and n ...

NoncentralChiSquareDistribution[\[Nu], \[Lambda]] represents a noncentral \[Chi]^2 distribution with \[Nu] degrees of freedom and noncentrality parameter \[Lambda].

MultivariateHypergeometricDistribution[n, {m_1, m_2, ..., m_k}] represents a multivariate hypergeometric distribution with n draws without replacement from a collection ...

Urn models have a long history, starting with Laplace suggesting in 1786 that France's population be estimated by an urn-sampling scheme. They are conceptually relatively ...

Distribution[l, set] lists the frequency of each element of set in list l.