DiscretePlot[expr, {n, n_max}] generates a plot of the values of expr when n runs from 1 to n_max.DiscretePlot[expr, {n, n_min, n_max}] generates a plot of the values of expr ...
By far the largest release since Version 1.0 in 1988, Version 6.0 added a remarkable breadth of new functionality. As well as introducing several major new fundamental ...
StableDistribution[type, \[Alpha], \[Beta], \[Mu], \[Sigma]] represents the stable distribution S_type with index of stability \[Alpha], skewness parameter \[Beta], location ...
CramerVonMisesTest[data] tests whether data is normally distributed using the Cramér\[Dash]von Mises test.CramerVonMisesTest[data, dist] tests whether data is distributed ...
WatsonUSquareTest[data] tests whether data is normally distributed using the Watson U^2 test.WatsonUSquareTest[data, dist] tests whether data is distributed according to dist ...
The ability to generate pseudorandom numbers is important for simulating events, estimating probabilities and other quantities, making randomized assignments or selections, ...
DensityHistogram[{{x_1, y_1}, {x_2, y_2}, ...}] plots a density histogram of the values {x_i, y_i}.DensityHistogram[{{x_1, y_1}, {x_2, y_2}, ...}, bspec] plots a density ...
FindDistributionParameters[data, dist] finds the parameter estimates for the distribution dist from data.FindDistributionParameters[data, dist, {{p, p_0}, {q, q_0}, ...}] ...
Statistical distributions have applications in many fields, including the biological, social, and physical sciences. Mathematica represents statistical distributions as ...
Integrate[f, x] gives the indefinite integral \[Integral]f d x. Integrate[f, {x, x_min, x_max}] gives the definite integral \[Integral]_x_min^x_max\ f\ d x. Integrate[f, {x, ...