Probability & Statistics with Quantities
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