The ability to generate pseudorandom numbers is important for simulating events, estimating probabilities and other quantities, making randomized assignments or selections, ...
ListLogPlot[{y_1, y_2, ...}] makes a log plot of the y_i, assumed to correspond to x coordinates 1, 2, ....ListLogPlot[{{x_1, y_1}, {x_2, y_2}, ...}] makes a log plot of the ...
ProductDistribution[dist_1, dist_2, ...] represents the joint distribution with independent component distributions dist_1, dist_2, ....
StableDistribution[type, \[Alpha], \[Beta], \[Mu], \[Sigma]] represents the stable distribution S_type with index of stability \[Alpha], skewness parameter \[Beta], location ...
The Mathematica compiler provides an important way both to speed up and also to work with Mathematica computations. It does this by taking assumptions about the computations ...
ListVectorPlot3D[array] generates a 3D vector plot from a 3D array of vector field values.ListVectorPlot3D[{{{x_1, y_1, z_1}, {vx_1, vy_1, vz_1}}, ...}] generates a 3D vector ...
ParallelArray[f, n] generates in parallel a list of length n, with elements f[i], evaluated.ParallelArray[f, {n_1, n_2, ...}] generates in parallel an n_1*n_2*... array of ...
An integration rule computes an estimate of an integral over a region, typically using a weighted sum. In the context of NIntegrate usage, an integration rule object provides ...
Mathematica stands out from traditional computer languages in supporting many programming paradigms. Procedural programming is the only paradigm available in languages like C ...
MATHEMATICA HOW TO Tutorials » Sequences of Operations Evaluation See Also » CompoundExpression More About » Language Overview Mathematica Syntax Procedural Programming ...