DifferenceDelta[f, i] gives the discrete difference \[DifferenceDelta]_i f = f(i + 1) - f(i).DifferenceDelta[f, {i, n}] gives the multiple difference DifferenceDelta[f, {i, ...

ExampleData["type"] gives a list of names of examples of the specified type.ExampleData[{" type", " name"}] gives the default form of the named example of the specified ...

LogNormalDistribution[\[Mu], \[Sigma]] represents a lognormal distribution derived from a normal distribution with mean \[Mu] and standard deviation \[Sigma].

Moment[list, r] gives the r\[Null]^th sample moment of the elements in list.Moment[dist, r] gives the r\[Null]^th moment of the symbolic distribution dist.Moment[..., {r_1, ...

NExpectation[expr, x \[Distributed] dist] gives the numerical expectation of expr under the assumption that x follows the probability distribution dist.NExpectation[expr, ...

PDF[dist, x] gives the probability density function for the symbolic distribution dist evaluated at x.PDF[dist, {x_1, x_2, ...}] gives the multivariate probability density ...

ProbabilityPlot[list] generates a plot of the CDF of list against the CDF of a normal distribution.ProbabilityPlot[dist] generates a plot of the CDF of the distribution dist ...

QuantilePlot[list] generates a plot of quantiles of list against the quantiles of a normal distribution.QuantilePlot[dist] generates a plot of quantiles of the distribution ...

Series[f, {x, x_0, n}] generates a power series expansion for f about the point x = x_0 to order (x - x_0) n. Series[f, {x, x_0, n_x}, {y, y_0, n_y}, ...] successively finds ...

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 ...