Documentation

Descriptive Statistics

Measures of central tendency, dispersion, shape, and correlation

Note

MuPAD® notebooks will be removed in a future release. Use MATLAB® live scripts instead.

To convert a MuPAD notebook file to a MATLAB live script file, see convertMuPADNotebook. MATLAB live scripts support most MuPAD functionality, although there are some differences. For more information, see Convert MuPAD Notebooks to MATLAB Live Scripts.

 numeric::gaussAGM Gauss' arithmetic geometric mean stats::correlation Correlation between data samples stats::correlationMatrix Compute the correlation matrix associated with a covariance matrix stats::covariance Covariance of data samples stats::cutoff Discard outliers stats::winsorize Clamp (winsorize) extremal values stats::frequency Tally numerical data into classes and count frequencies stats::geometricMean Geometric mean of a data sample stats::harmonicMean Harmonic mean of a data sample stats::kurtosis Kurtosis (excess) of a data sample stats::mean Arithmetic mean of a data sample stats::meandev Mean deviation of a data sample stats::median Median value of a data sample stats::modal Modal (most frequent) value(s) in a data sample stats::moment The K-th moment of a data sample stats::obliquity Obliquity (skewness) of a data sample stats::quadraticMean Quadratic mean of a data sample stats::stdev Standard deviation of a data sample stats::variance Variance of a data sample

Topics

Store Statistical Data

MuPAD offers various data containers, such as lists, arrays, tables, and so on, to store and organize data.

Compute Measures of Central Tendency

Measures of central tendency locate a distribution of data along an appropriate scale.

Compute Measures of Dispersion

The measures of dispersion summarize how spread out (or scattered) the data values are on the number line.

Compute Measures of Shape

The measures of shape indicate the symmetry and flatness of the distribution of a data sample.

Compute Covariance and Correlation

If you have two or more data samples with an equal number of elements, you can estimate how similar these data samples are.

Handle Outliers

The outliers are data points located far outside the range of the majority of the data.

Bin Data

The stats::frequency function categorizes the numerical data into a number of bins given by semiopen intervals (ai, bi].

Mathematical Modeling with Symbolic Math Toolbox

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