TTest
(Built-in Mathematica Symbol) 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 ...
AndersonDarlingTest[data] tests whether data is normally distributed using the Anderson\[Dash]Darling test.AndersonDarlingTest[data, dist] tests whether data is distributed ...
VarianceEquivalenceTest[{data_1, data_2, ...}] tests whether the variances of the data_i are equal. VarianceEquivalenceTest[{data_1, ...}, " property"] returns the value of " ...
SmoothKernelDistribution[{x_1, x_2, ...}] represents a smooth kernel distribution based on the data values x_i.SmoothKernelDistribution[{{x_1, y_1, ...}, {x_2, y_2, ...}, ...
InterpolationPoints is an option to SmoothKernelDistribution and FunctionInterpolation that specifies the initial number of interpolation points to use.
LocationTest[data] tests whether the mean or median of the data is zero. LocationTest[{data_1, data_2}] tests whether the means or medians of data_1 and data_2 are ...
DistributionFitTest[data] tests whether data is normally distributed. DistributionFitTest[data, dist] tests whether data is distributed according to dist. ...
MardiaCombinedTest[data] tests whether data follows a MultinormalDistribution using the Mardia combined test.MardiaCombinedTest[data, " property"] returns the value of " ...
ShapiroWilkTest[data] tests whether data is normally distributed using the Shapiro\[Dash]Wilk test.ShapiroWilkTest[data, " property"] returns the value of " property".
SignificanceLevel is an option to VarianceTest and similar functions that controls cutoffs for diagnostic tests as well as test conclusions.