ContinuousWaveletTransform[{x_1, x_2, ...}] gives the continuous wavelet transform of a list of values x_i.ContinuousWaveletTransform[data, wave] gives the continuous wavelet ...

EdgeCount[g] gives a count of the number of edges in the graph g.EdgeCount[g, patt] gives a count of the number of edges that match the pattern patt.

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 ...

Monitor[expr, mon] generates a temporary monitor cell in which the continually updated current value of mon is displayed during the course of evaluation of expr.

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 ...

SetterBar[x, {val_1, val_2, ...}] represents a setter bar with setting x and with setter buttons for values val_i.SetterBar[Dynamic[x], {val_1, val_2, ...}] takes the setting ...

BubbleChart[{{x_1, y_1, z_1}, {x_2, y_2, z_2}, ...}] makes a bubble chart with bubbles at positions {x_i, y_i} with sizes z_i.BubbleChart[{..., w_i[{x_i, y_i, z_i}, ...], ...

EvaluationMonitor is an option for various numerical computation and plotting functions that gives an expression to evaluate whenever functions derived from the input are ...

NegativeMultinomialDistribution[n, p] represents a negative multinomial distribution with parameter n and failure probability vector p.

PearsonChiSquareTest[data] tests whether data is normally distributed using the Pearson \[Chi]^2 test.PearsonChiSquareTest[data, dist] tests whether data is distributed ...