Descriptive Statistics

Numerical summaries and associated measures

Compute descriptive statistics from sample data, including measures of central tendency, dispersion, shape, correlation, and covariance. Tabulate and cross-tabulate data, and compute summary statistics for grouped data.


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geomeanGeometric mean
harmmeanHarmonic mean
trimmeanMean, excluding outliers
momentCentral moment
rangeRange of values
iqrInterquartile range
madMean or median absolute deviation
prctilePercentiles of a data set
quantileQuantiles of a data set
zscoreStandardized z-scores
corrLinear or rank correlation
robustcovRobust multivariate covariance and mean estimate
cholcovCholesky-like covariance decomposition
corrcovConvert covariance matrix to correlation matrix
partialcorrLinear or rank partial correlation coefficients
partialcorriPartial correlation coefficients adjusted for internal variables
nearcorrCompute nearest correlation matrix by minimizing Frobenius distance
grpstatsSummary statistics organized by group
tabulateFrequency table
tiedrankRank adjusted for ties


Exploratory Analysis of Data

Explore the distribution of data using descriptive statistics.

Measures of Central Tendency

Locate a distribution of data along an appropriate scale.

Measures of Dispersion

Find out how spread out the data values are on the number line.

Quantiles and Percentiles

Learn how the Statistics and Machine Learning Toolbox™ computes quantiles and percentiles.

Grouping Variables

Grouping variables are utility variables used to group or categorize observations.