There are a variety of ways to describe probability distributions such as probability density or mass, cumulative versions of density and mass, inverses of the cumulative ...

Mathematica's symbolic architecture makes possible a uniquely convenient approach to working with statistical models. Starting from arbitrary data, Mathematica generates ...

A variety of moments or combinations of moments are used to summarize a distribution or data. Mean is used to indicate a center location, variance and standard deviation are ...

Statistical visualization is used to understand how data is distributed and how that compares to other datasets and distributions. Histograms and smooth histograms both ...

Mathematica integrates many aspects of statistical data analysis, from getting and exploring data to building high-quality models and and deducing consequences. Mathematica ...

Integrated into the core Mathematica language is industrial-strength string manipulation, not only with ordinary regular expressions, but also with Mathematica's own powerful ...

Mathematica incorporates the latest highly efficient algorithms to allow operations on strings with millions of elements, all making use of Mathematica's unique symbolic ...

Mathematica's symbolic string patterns provide a compact yet readable basis for sophisticated string operations. Included directly in programs, or symbolically generated on ...

Mathematica's unified symbolic architecture immediately allows it to perform structural transformations not only on objects like lists, but also on general symbolic ...

Mathematica provides built-in functions for generating standard structure matrices and convolution kernels in any number of dimensions, in a form that can be used directly in ...