BrownForsytheTest[data] tests whether the variance of data is 1. BrownForsytheTest[{data_1, data_2}] tests whether the variances of data_1 and data_2 are ...
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, ...
KolmogorovSmirnovTest[data] tests whether data is normally distributed using the Kolmogorov\[Dash]Smirnov test.KolmogorovSmirnovTest[data, dist] tests whether data is ...
PairedZTest[data] tests whether the mean of the data is zero. PairedZTest[{data_1, data_2}] tests whether the means of data_1 and data_2 are equal.PairedZTest[dspec, ...
Based on original algorithms developed at Wolfram Research, Mathematica's core randomness generation is both highly efficient and of exceptional quality. Mathematica can ...
Likelihood[dist, {x_1, x_2, ...}] gives the likelihood function for observations x_1, x_2, ... from the distribution dist.
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 ...
HypothesisTestData[...] represents hypothesis test data such as generated by DistributionFitTest, AndersonDarlingTest, etc.
PairedTTest[data] tests whether the mean of data is zero. PairedTTest[{data_1, data_2}] tests whether the mean of data_1\[Dash] data_2 is zero.PairedTTest[dspec, \[Mu]_0] ...
LogLikelihood[dist, {x_1, x_2, ...}] gives the log-likelihood function for observations x_1, x_2, ... from the distribution dist.