Distribute[f[x_1, x_2, ...]] distributes f over Plus appearing in any of the x_i. Distribute[expr, g] distributes over g. Distribute[expr, g, f] performs the distribution ...

Distributed[x, dist] or x \[Distributed] dist asserts that the random variable x is distributed according to the probability distribution dist. Distributed[{x_1, x_2, ...}, ...

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

The fundamental type of distribution in reliability analysis is a lifetime distribution. This models the lifetime of a component or a system. Many lifetime distributions are ...

Derived distributions are modifications to existing distributions. There is a variety of ways in which you can arrive at modified distributions, including functions of random ...

Just as normal and stable distributions are natural limit distributions when considering linear combinations such as means of independent variables, extreme value ...

There are a variety of ways to describe probability distributions such as probability density or mass, cumulative versions of density and mass, inverses of the cumulative ...

DistributedContexts is an option for various parallel computing functions that specifies which definitions for symbols appearing in an expression should be distributed to all ...

Heavy tail means that there is a larger probability of getting very large values. So heavy tail distributions typically represent wild as opposed to mild randomness. An ...

$DistributedContexts is the default value of the DistributedContexts option of functions such as ParallelTable and ParallelMap.