EstimatedDistribution[data, dist] estimates the parametric distribution dist from data.EstimatedDistribution[data, dist, {{p, p_0}, {q, q_0}, ...}] estimates the parameters ...
NIntegrate[f, {x, x_min, x_max}] gives a numerical approximation to the integral \[Integral]_x_min^x_max\ f\ d \ x. NIntegrate[f, {x, x_min, x_max}, {y, y_min, y_max}, ...] ...
RandomVariate[dist] gives a pseudorandom variate from the symbolic distribution dist.RandomVariate[dist, n] gives a list of n pseudorandom variates from the symbolic ...
ContourPlot[f, {x, x_min, x_max}, {y, y_min, y_max}] generates a contour plot of f as a function of x and y. ContourPlot[f == g, {x, x_min, x_max}, {y, y_min, y_max}] plots ...
Sum
(Built-in Mathematica Symbol) 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, ...
Mathematica 6.0 fundamentally redefined Mathematica and introduced a major new paradigm for computation. Building on Mathematica's time-tested core symbolic architecture, ...
This package contains functions for computing confidence intervals from data and p-values and confidence intervals for distributions related to the normal distribution. Given ...
BrownForsytheTest[data] tests whether the variance of data is 1. BrownForsytheTest[{data_1, data_2}] tests whether the variances of data_1 and data_2 are ...
Exp
(Built-in Mathematica Symbol) Exp[z] gives the exponential of z.
SignedRankTest[data] tests whether the median of data is zero. SignedRankTest[{data_1, data_2}] tests whether the median of data_1 - data_2 is zero.SignedRankTest[dspec, ...