NExpectation[expr, x \[Distributed] dist] gives the numerical expectation of expr under the assumption that x follows the probability distribution dist. NExpectation[expr, ...

Conditioned[expr, cond] or expr \[Conditioned] cond represents expr conditioned by the predicate cond.

Random graphs following a distribution model the mechanism by which the graph is formed, such as adding links to a web page or citations to a paper. These distributions make ...

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, ...}, ...

Probability and statistics are used to model uncertainty from a variety of sources, such as incomplete or simplified models. Yet you can build useful models for aggregate or ...

Social networks represent relationships involving social entities such as friendships among individuals, communication in a group, or transactions between corporations. ...

GlobalClusteringCoefficient[g] gives the global clustering coefficient of the graph g.

MeanClusteringCoefficient[g] gives the mean clustering coefficient of the graph g.

A random variable unlike a normal variable doesn't have a specific value, but rather a range of values and a densitity that gives different probabilities of obtaining values ...

GraphPropertyDistribution[expr, x \[Distributed] gdist] represents the distribution of the property expr where the random variable x follows the graph distribution gdist. ...