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 ...

EstimatedDistribution (Built-in Mathematica Symbol)

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

NormalDistribution (Built-in Mathematica Symbol)

NormalDistribution[\[Mu], \[Sigma]] represents a normal (Gaussian) distribution with mean \[Mu] and standard deviation \[Sigma].NormalDistribution[] represents a normal ...

UniformDistribution (Built-in Mathematica Symbol)

UniformDistribution[{min, max}] represents a continuous uniform statistical distribution giving values between min and max. UniformDistribution[] represents a uniform ...

Fibonacci (Built-in Mathematica Symbol)

Fibonacci[n] gives the Fibonacci number F_n. Fibonacci[n, x] gives the Fibonacci polynomial F_n (x).

InterpolatingPolynomial (Built-in Mathematica Symbol)

InterpolatingPolynomial[{f_1, f_2, ...}, x] constructs an interpolating polynomial in x which reproduces the function values f_i at successive integer values 1, 2, ... of x. ...

Outer (Built-in Mathematica Symbol)

Outer[f, list_1, list_2, ...] gives the generalized outer product of the list_i, forming all possible combinations of the lowest-level elements in each of them, and feeding ...

ProductLog (Built-in Mathematica Symbol)

ProductLog[z] gives the principal solution for w in z == w e^w. ProductLog[k, z] gives the k\[Null]^th solution.

SlideView (Built-in Mathematica Symbol)

SlideView[{expr_1, expr_2, ...}] represents an object in which the expr_i are set up to be displayed on successive slides. SlideView[{expr_1, expr_2, ...}, i] makes the ...

TriangularDistribution (Built-in Mathematica Symbol)

TriangularDistribution[{min, max}] represents a symmetric triangular statistical distribution giving values between min and max. TriangularDistribution[{min, max}, c] ...