BinCounts[{x_1, x_2, ...}] counts the number of elements x_i whose values lie in successive integer bins.BinCounts[{x_1, x_2, ...}, dx] counts the number of elements x_i ...

KernelMixtureDistribution[{x_1, x_2, ...}] represents a kernel mixture distribution based on the data values x_i.KernelMixtureDistribution[{{x_1, y_1, ...}, {x_2, y_2, ...}, ...

ImageLevels[image] gives a list of pixel values and counts for each channel in image. ImageLevels[image, n] bins pixel values into n equally spaced levels.ImageLevels[image, ...

Mathematica efficiently implements state-of-the-art data classification algorithms, allowing you to visualize distributions, search for nearest neighbors, and do cluster ...

Mathematica 8 adds a number of new areas for visualization, including statistical, financial, wavelet, and control-related visualizations. These areas all provide a high ...

HistogramList[{x_1, x_2, ...}] gives a list of bins and histogram heights of the values x_i.HistogramList[{{x_1, y_1, ...}, {x_2, y_2, ...}, ...}] gives a list of bins and ...

Mathematica's descriptive statistics functions operate both on explicit data and on symbolic representations of statistical distributions. When operating on explicit data, ...

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

LogPlot, ListLogPlot, and related functions have been added to the built-in Mathematica kernel. PolarPlot and ListPolarPlot have been added to the built-in Mathematica ...

Huge numerical datasets are routine for Mathematica. Its powerful array primitives make large-scale array manipulation both easy to specify and highly efficient. And its ...