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 ...

Mathematica 9 adds major extensions for visualization. Legends are standard across visualization functions and are easily extended to custom graphics. Data with units can be ...

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

A random variable unlike a normal variable doesn't have a specific value, but rather a range of values and a densitity that gives different probabilities of obtaining values ...

SmoothDensityHistogram[{{x_1, y_1}, {x_2, y_2}, ...}] plots a smooth kernel histogram of the values {x_i, y_i}. SmoothDensityHistogram[{{x_1, y_1}, {x_2, y_2}, ...}, espec] ...

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 ...

Integration of Wolfram|Alpha into Mathematica,

Units >, Quantity — represents a value associated with a unit, UnitConvert — convert between different units and unit systems, QuantityMagnitude — give the value associated ...

SmoothHistogram3D[{{x_1, y_1}, {x_2, y_2}, ...}] plots a 3D smooth kernel histogram of the values {x_i, y_i}. SmoothHistogram3D[{{x_1, y_1}, {x_2, y_2}, ...}, espec] plots a ...