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Building Large Software Systems in ...   (Mathematica Tutorial)
Building large software systems in Mathematica should follow the general principles that apply to building any large software system. The details may be unique to Mathematica ...
NIntegrate Integration Rules   (Mathematica Tutorial)
An integration rule computes an estimate of an integral over a region, typically using a weighted sum. In the context of NIntegrate usage, an integration rule object provides ...
ProbabilityScalePlot   (Built-in Mathematica Symbol)
ProbabilityScalePlot[{x_1, x_2, ...}] generates a normal probability plot of the samples x_i. ProbabilityScalePlot[{x_1, x_2, ...}, " dist"] generates a probability plot ...
NIntegrate Introduction   (Mathematica Tutorial)
The Mathematica function NIntegrate is a general numerical integrator. It can handle a wide range of one-dimensional and multidimensional integrals. Finding a numerical ...
Summary of New Features in 6.0   (Mathematica Guide)
Mathematica 6.0 fundamentally redefined Mathematica and introduced a major new paradigm for computation. Building on Mathematica's time-tested core symbolic architecture, ...
NIntegrate Integration Strategies   (Mathematica Tutorial)
An integration strategy is an algorithm that attempts to compute integral estimates that satisfy user-specified precision or accuracy goals. An integration strategy normally ...
BindEvent   (GUIKit Package Symbol)
BindEvent[name | {target, name} | {target, name, filter}, object | script | call, ...] binds an event from one object to a listener or to a script.
Plot Diagnostics for Fitted Models   (Mathematica How To)
Diagnostics are an important part of analyzing models of data. Plots of residuals and leverage or influence measures provide valuable insight into whether assumptions of the ...
BernoulliDistribution   (Built-in Mathematica Symbol)
BernoulliDistribution[p] represents a Bernoulli distribution with probability parameter p.
DavisDistribution   (Built-in Mathematica Symbol)
DavisDistribution[b, n, \[Mu]] represents a Davis distribution with scale parameter b, shape parameter n, and location parameter \[Mu].
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