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ConoverTest   (Built-in Mathematica Symbol)
ConoverTest[{data_1, data_2}] tests whether the variances of data_1 and data_2 are equal.ConoverTest[dspec, \[Sigma]_0^2] tests a dispersion measure against ...
SiegelTukeyTest   (Built-in Mathematica Symbol)
SiegelTukeyTest[{data_1, data_2}] tests whether the variances of data_1 and data_2 are equal.SiegelTukeyTest[dspec, \[Sigma]_0^2] tests a dispersion measure against ...
MixtureDistribution   (Built-in Mathematica Symbol)
MixtureDistribution[{w_1, ..., w_n}, {dist_1, ..., dist_n}] represents a mixture distribution whose CDF is given as a sum of the CDFs of the component distributions dist_i, ...
MannWhitneyTest   (Built-in Mathematica Symbol)
MannWhitneyTest[{data_1, data_2}] tests whether the medians of data_1 and data_2 are equal.MannWhitneyTest[dspec, \[Mu]_0] tests the median difference against ...
ZTest   (Built-in Mathematica Symbol)
ZTest[data] tests whether the mean of the data is zero. ZTest[{data_1, data_2}] tests whether the means of data_1 and data_2 are equal.ZTest[dspec, \[Sigma]] tests for zero ...
ProbabilityPlot   (Built-in Mathematica Symbol)
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 ...
NormalPValue   (Hypothesis Testing Package Symbol)
NormalPValue[x] gives the cumulative density beyond x for a normal distribution with zero mean and unit variance.
SignificanceLevel   (Built-in Mathematica Symbol)
SignificanceLevel is an option to VarianceTest and similar functions that controls cutoffs for diagnostic tests as well as test conclusions.
FisherRatioTest   (Built-in Mathematica Symbol)
FisherRatioTest[data] tests whether the variance of data is one. FisherRatioTest[{data_1, data_2}] tests whether the variances of data_1 and data_2 are ...
Histogram   (Built-in Mathematica Symbol)
Histogram[{x_1, x_2, ...}] plots a histogram of the values x_i.Histogram[{x_1, x_2, ...}, bspec] plots a histogram with bin width specification bspec.Histogram[{x_1, x_2, ...
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