There are many types of distributions that are relevant for communication systems. In telecom, for instance, exponential and Erlang distributions modeling talk lengths are ...
DistributionParameterQ[dist] yields True if dist is a valid distribution, and yields False otherwise.
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] ...
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 ...
ProductDistribution[dist_1, dist_2, ...] represents the joint distribution with independent component distributions dist_1, dist_2, ....
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 ...
SignTest[data] tests whether the median of data is zero. SignTest[{data_1, data_2}] tests whether the median of data_1\[Dash] data_2 is zero.SignTest[dspec, \[Mu] 0] tests a ...
VarianceEquivalenceTest[{data_1, data_2, ...}] tests whether the variances of the data_i are equal. VarianceEquivalenceTest[{data_1, ...}, " property"] returns the value of " ...
HalfNormalDistribution[\[Theta]] represents a half-normal distribution with scale inversely proportional to parameter \[Theta].
InverseSurvivalFunction[dist, q] gives the inverse of the survival function for the symbolic distribution dist as a function of the variable q.