PairedHistogram[{x_1, x_2, ...}, {y_1, y_2, ...}] plots a paired histogram of the values x_i and y_i.PairedHistogram[{x_1, x_2, ...}, {y_1, y_2, ...}, bspec] plots a paired ...

Histogram3D[{{x_1, y_1}, {x_2, y_2}, ...}] plots a 3D histogram of the values {x_i, y_i}.Histogram3D[{{x_1, y_1}, {x_2, y_2}, ...}, bspec] plots a 3D histogram with bins ...

Monte Carlo methods use randomly generated numbers or events to simulate random processes and estimate complicated results. For example, they are used to model financial ...

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, ...}, ...

ParameterEstimator is an option to EstimatedDistribution and FindDistributionParameters that specifies what parameter estimator to use.

BernoulliDistribution[p] represents a Bernoulli distribution with probability parameter p.

RandomImage[max, {w, h}] gives an image of dimensions {w, h} with pseudorandom pixel values generated from a uniform distribution in the range 0 to max.RandomImage[{min, ...

Statistical distributions have applications in many fields, including the biological, social, and physical sciences. Mathematica represents statistical distributions as ...

EstimatedDistribution[data, dist] estimates the parametric distribution dist from data.EstimatedDistribution[data, dist, {{p, p_0}, {q, q_0}, ...}] estimates the parameters ...

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 ...