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ShapiroWilkTest   (Built-in Mathematica Symbol)
ShapiroWilkTest[data] tests whether data is normally distributed using the Shapiro\[Dash]Wilk test.ShapiroWilkTest[data, " property"] returns the value of " property".
OpenCLLink Programming   (OpenCLLink Tutorial)
Programming OpenCL in Mathematica is simple since the user need not write C wrapper code—which can be quite verbose, difficult to understand, and hard to debug. Using ...
Formatting   (SymbolicC Tutorial)
SymbolicC provides automated formatting of the generated C output. This section reviews some of the ways that you can work with formatting to create your own styles of ...
Fit   (Built-in Mathematica Symbol)
Fit[data, funs, vars] finds a least-squares fit to a list of data as a linear combination of the functions funs of variables vars.
GraphLayout   (Built-in Mathematica Symbol)
GraphLayout is an option to Graph and related functions that specifies what layout to use for graph components and collections of components.
Descriptive Statistics   (Mathematica Tutorial)
Descriptive statistics refers to properties of distributions, such as location, dispersion, and shape. The functions described here compute descriptive statistics of lists of ...
Discrete Distributions   (Mathematica Tutorial)
The functions described here are among the most commonly used discrete univariate statistical distributions. You can compute their densities, means, variances, and other ...
Symbolic Parameters and Inexact ...   (Mathematica Tutorial)
The differential equations that arise in practice are of two types. Here is an example of the first type. Here is an example of the second type. This equation has a symbolic ...
MusicScale   (Music Package Symbol)
MusicScale[{i_1, i_2, ...}, freq, dur] creates a Sound object that is a sequence of pitches corresponding to numbers i_1, i_2, ..., a list of intervals measured in cents, ...
EulerSum   (Numerical Calculus Package Symbol)
EulerSum[f, {i, i_min, i_max}] gives a numerical approximation to the sum \[Sum]i = i_min i_max f using Euler's transformation.EulerSum[f, {i, i_min, i_max, di}] uses a step ...
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