VarianceTest[data] tests whether the variance of the data is one. VarianceTest[{data_1, data_2}] tests whether the variances of data_1 and data_2 are ...

DensityPlot[f, {x, x_min, x_max}, {y, y_min, y_max}] makes a density plot of f as a function of x and y.

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

FindFit[data, expr, pars, vars] finds numerical values of the parameters pars that make expr give a best fit to data as a function of vars. The data can have the form {{x_1, ...

Integrate[f, x] gives the indefinite integral \[Integral]f d x. Integrate[f, {x, x_min, x_max}] gives the definite integral \[Integral]_x_min^x_max\ f\ d x. Integrate[f, {x, ...

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 ...

NProbability[pred, x \[Distributed] dist] gives the numerical probability for an event that satisfies the predicate pred under the assumption that x follows the probability ...

Plot3D[f, {x, x_min, x_max}, {y, y_min, y_max}] generates a three-dimensional plot of f as a function of x and y. Plot3D[{f_1, f_2, ...}, {x, x_min, x_max}, {y, y_min, ...

TTest[data] tests whether the mean of data is zero. TTest[{data_1, data_2}] tests whether the means of data_1 and data_2 are equal.TTest[dspec, \[Mu]_0] tests the mean ...