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MomentConvert   (Built-in Mathematica Symbol)
MomentConvert[mexpr, form] converts the moment expression mexpr to the specified form.
AndersonDarlingTest   (Built-in Mathematica Symbol)
AndersonDarlingTest[data] tests whether data is normally distributed using the Anderson\[Dash]Darling test.AndersonDarlingTest[data, dist] tests whether data is distributed ...
RectangleChart   (Built-in Mathematica Symbol)
RectangleChart[{{x_1, y_1}, {x_2, y_2}, ...}] makes a rectangle chart with bars of width x_i and height y_i. RectangleChart[{..., w_i[{x_i, y_i}, ...], ..., w_j[{x_i, y_j}, ...
Alphabetical Listing   (Mathematica Guide)
Mathematica has over 3000 built-in functions and other objects, all based on a single unified framework, and all carefully designed to work together, both in simple ...
MixtureDistribution   (Built-in Mathematica Symbol)
MixtureDistribution[{w_1, ..., w_n}, {dist_1, ..., dist_n}] represents a mixture distribution whose CDF is given as a sum of the CDFs of the component distributions dist_i, ...
NExpectation   (Built-in Mathematica Symbol)
NExpectation[expr, x \[Distributed] dist] gives the numerical expectation of expr under the assumption that x follows the probability distribution dist.NExpectation[expr, ...
ProductDistribution   (Built-in Mathematica Symbol)
ProductDistribution[dist_1, dist_2, ...] represents the joint distribution with independent component distributions dist_1, dist_2, ....
When building an initial statistical model, you may not have a good idea of what parametric distribution family it should come from. Nonparametric distributions make very few ...
Statistical Distribution Functions   (Mathematica Guide)
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 ...
Expectation   (Built-in Mathematica Symbol)
Expectation[expr, x \[Distributed] dist] gives the expectation of expr under the assumption that x follows the probability distribution dist. Expectation[expr, x ...
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