ListContourPlot[array] generates a contour plot from an array of height values. ListContourPlot[{{x_1, y_1, f_1}, {x_2, y_2, f_2}, ...}] generates a contour plot from values ...
ListDensityPlot[array] generates a smooth density plot from an array of values. ListDensityPlot[{{x_1, y_1, f_1}, {x_2, y_2, f_2}, ...}] generates a density plot with values ...
ListLinePlot[{y_1, y_2, ...}] plots a line through a list of values, assumed to correspond to x coordinates 1, 2, .... ListLinePlot[{{x_1, y_1}, {x_2, y_2}, ...}] plots a ...
ListLogPlot[{y_1, y_2, ...}] makes a log plot of the y_i, assumed to correspond to x coordinates 1, 2, ....ListLogPlot[{{x_1, y_1}, {x_2, y_2}, ...}] makes a log plot of the ...
ListPlot[{y_1, y_2, ...}] plots points corresponding to a list of values, assumed to correspond to x coordinates 1, 2, .... ListPlot[{{x_1, y_1}, {x_2, y_2}, ...}] plots a ...
LocationEquivalenceTest[{data_1, data_2, ...}] tests whether the means or medians of the data_i are equal. LocationEquivalenceTest[{data_1, ...}, " property"] returns the ...
MarginalDistribution[dist, k] represents a univariate marginal distribution of the k\[Null]^th coordinate from the multivariate distribution dist.MarginalDistribution[dist, ...
MomentConvert[mexpr, form] converts the moment expression mexpr to the specified form.
NonlinearModelFit[{y_1, y_2, ...}, form, {\[Beta]_1, ...}, x] constructs a nonlinear model with structure form that fits the y_i for successive x values 1, 2, ... using the ...
NormalDistribution[\[Mu], \[Sigma]] represents a normal (Gaussian) distribution with mean \[Mu] and standard deviation \[Sigma].NormalDistribution[] represents a normal ...