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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 ...
PairedBarChart   (Built-in Mathematica Symbol)
PairedBarChart[{y_1, y_2, ...}, {z_1, z_2, ...}] makes a paired bar chart with bar lengths y_1, y_2, ... and z_1, z_2, ..., respectively.PairedBarChart[{..., w_i[y_i, ...], ...
ListPolarPlot   (Built-in Mathematica Symbol)
ListPolarPlot[{r_1, r_2, ...}] plots points equally spaced in angle at radii r_i.ListPolarPlot[{{\[Theta]_1, r_1}, {\[Theta]_2, r_2}, ...}] plots points at polar coordinates ...
LogLogPlot   (Built-in Mathematica Symbol)
LogLogPlot[f, {x, x_min, x_max}] generates a log-log plot of f as function of x from x_min to x_max. LogLogPlot[{f_1, f_2, ...}, {x, x_min, x_max}] generates log-log plots of ...
PoissonDistribution   (Built-in Mathematica Symbol)
PoissonDistribution[\[Mu]] represents a Poisson distribution with mean \[Mu].
CensoredDistribution   (Built-in Mathematica Symbol)
CensoredDistribution[{x_min, x_max}, dist] represents the distribution of values that come from dist and are censored to be between x_min and ...
ListPointPlot3D   (Built-in Mathematica Symbol)
ListPointPlot3D[{{x_1, y_1, z_1}, {x_2, y_2, z_2}, ...}] generates a 3D scatter plot of points with coordinates {x_i, y_i, z_i}. ListPointPlot3D[array] generates a 3D scatter ...
SmoothHistogram3D   (Built-in Mathematica Symbol)
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 ...
SmoothHistogram   (Built-in Mathematica Symbol)
SmoothHistogram[{x_1, x_2, ...}] plots a smooth kernel histogram of the values x_i.SmoothHistogram[{x_1, x_2, ...}, espec] plots a smooth kernel histogram with estimator ...
BinormalDistribution   (Built-in Mathematica Symbol)
BinormalDistribution[{\[Mu]_1, \[Mu]_2}, {\[Sigma]_1, \[Sigma]_\ 2}, \[Rho]] represents a bivariate normal distribution with mean {\[Mu]_1, \[Mu]_2} and covariance matrix ...
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