The Wolfram Language's descriptive statistics functions operate both on explicit data and on symbolic representations of statistical distributions. When operating on explicit data, the functions routinely handle huge datasets, which can contain not only numbers but also symbolic elements representing, for example, parametrized or unknown data.

Location Statistics

Mean   ▪ Median   ▪ Commonest   ▪ TrimmedMean   ▪ WinsorizedMean   ▪ BiweightLocation   ▪ SpatialMedian   ▪ CentralFeature   ▪ HarmonicMean   ▪ GeometricMean   ▪ ContraharmonicMean

Dispersion Statistics

Variance   ▪ TrimmedVariance   ▪ WinsorizedVariance   ▪ StandardDeviation   ▪ MeanDeviation   ▪ MedianDeviation   ▪ QuartileDeviation   ▪ InterquartileRange   ▪ QnDispersion   ▪ SnDispersion   ▪ BiweightMidvariance

Shape Statistics

Skewness   ▪ Kurtosis   ▪ QuartileSkewness   ▪ Entropy   ▪ EstimatedDistribution

Dependency Statistics

Covariance   ▪ Correlation   ▪ AbsoluteCorrelation   ▪ SpearmanRho   ▪ KendallTau   ▪ HoeffdingD   ▪ GoodmanKruskalGamma   ▪ BlomqvistBeta   ▪ WilksW   ▪ PillaiTrace

Spatial Point Statistics »

MeanPointDensity   ▪ PointDensity   ▪ HistogramPointDensity   ▪ SmoothPointDensity   ▪ RipleyK   ▪ BesagL   ▪ EmptySpaceF   ▪ NearestNeighborG   ▪ PairCorrelationG   ▪ SpatialJ

General Statistics

Moment   ▪ CentralMoment   ▪ FactorialMoment   ▪ Cumulant   ▪ RootMeanSquare   ▪ Expectation   ▪ Probability   ▪ BinCounts

Order Statistics

Min   ▪ Max   ▪ MinMax   ▪ Sort   ▪ Ordering   ▪ RankedMin   ▪ RankedMax   ▪ Quantile   ▪ Quartiles   ▪ TakeLargest   ▪ TakeSmallest

Data Models

WeightedData   ▪ EventData   ▪ TimeSeries   ▪ EventSeries   ▪ TemporalData   ▪ SpatialPointData   ▪ SpatialBinnedPointData

Symbolic Features of Distributions

CDF   ▪ PDF   ▪ InverseCDF   ▪ CharacteristicFunction

Statistical Visualization »

Histogram   ▪ Histogram3D   ▪ QuantilePlot   ▪ BoxWhiskerChart   ▪ ...