Mathematica has three functions for generating pseudorandom numbers that are distributed uniformly over a range of values. Pseudorandom number generation. Generating tables ...

HazardFunction[dist, x] gives the hazard function for the symbolic distribution dist evaluated at x.HazardFunction[dist, {x_1, x_2, ...}] gives the multivariate hazard ...

Quantile[list, q] gives the q\[Null]\[Null]^th quantile of list. Quantile[list, {q_1, q_2, ...}] gives a list of quantiles q_1, q_2, .... Quantile[list, q, {{a, b}, {c, d}}] ...

The ability to generate pseudorandom numbers is important for simulating events, estimating probabilities and other quantities, making randomized assignments or selections, ...

DiscretePlot3D[expr, {i, i_min, i_max}, {j, j_min, j_max}] generates a plot of the values of expr when i runs from i_min to i_max and j runs from j_min to ...

GeneralizedLinearModelFit[{y_1, y_2, ...}, {f_1, f_2, ...}, x] constructs a generalized linear model of the form g -1 (\[Beta]_0 + \[Beta]_1 f_1 + \[Beta]_2 f_2 + ...) that ...

Histogram[{x_1, x_2, ...}] plots a histogram of the values x_i.Histogram[{x_1, x_2, ...}, bspec] plots a histogram with bin width specification bspec.Histogram[{x_1, x_2, ...

Mathematica has over 3000 built-in functions and other objects, all based on a single unified framework, and all carefully designed to work together, both in simple ...

Sum[f, {i, i_max}] evaluates the sum \[Sum]i = 1 i_max f. Sum[f, {i, i_min, i_max}] starts with i = i_min. Sum[f, {i, i_min, i_max, di}] uses steps d i. Sum[f, {i, {i_1, i_2, ...

As of Version 8.0, ExpectedValue has been superseded by Expectation and NExpectation.