In everyday language, you use quantities with probability and statistics concepts surprisingly often, e.g. height distribution, cost distribution, temperature distribution, or for that matter mean weight or median voltage. It is typically because you deal with a whole collection of values perhaps from many measurements or simply many things.  The Wolfram Language provides extensive support for both probability and statistics, as well as quantities and their integrated use. Data and distributions can have units, and all their subsequent manipulation will automatically support the automatic propagation and conversion as needed.

Descriptive Statistics »

Mean — compute descriptive statistics for quantity data

Median  ▪  StandardDeviation  ▪  Covariance  ▪  ...

Statistical Visualization »

Histogram — visualize statistical data with quantities

SmoothHistogram  ▪  QuantilePlot  ▪  ListPlot  ▪  ...

Distributions of Quantities

QuantityDistribution — a distribution of quantities

EmpiricalDistribution  ▪  SmoothKernelDistribution  ▪  ...

Parametric Distributions »

NormalDistribution — use quantity parameters in distributions

ExponentialDistribution  ▪  BinormalDistribution  ▪  ...

Derived Distributions »

TransformedDistribution — build distributions from quantity variables and distributions

MixtureDistribution  ▪  TruncatedDistribution  ▪  ...

Hypothesis Testing »

LocationTest — test hypotheses for quantity data and distributions

DistributionFitTest  ▪  IndependenceTest  ▪  ...

Estimation & Simulation

EstimatedDistribution — estimate distributions from quantity data

RandomVariate — generate data from quantity distributions

Probability & Expectation »

Expectation — compute expected quantities

Probability  ▪  NExpectation  ▪  NProbability  ▪  ...

Unit Manipulation »

Quantity — represent a quantity

UnitConvert — convert units for quantity data and distributions

UnitSimplify  ▪  QuantityMagnitude  ▪  QuantityUnit  ▪  ...