skewness — Compute sample skewness.

skewness(X) computes biased sample skewness along the first non-singleton dimension. skewness(X,0,...) applies the bias correction. Dimension, vector-dimension, and "all" forms are supported.

Syntax

Y = skewness(X)
Y = skewness(X, flag)
Y = skewness(X, flag, dim)

Inputs

NameTypeRequiredDefaultDescription
XAnyYesInput data array.
flagNumericArrayNoNormalization or deviation mode flag.
dimAnyNoDimension, dimension vector, or "all" selector.
optionsAnyVariadicOptional dimension and missing-value arguments.

Returns

NameTypeDescription
YNumericArrayComputed statistic.

Errors

IdentifierWhenMessage
RunMat:skewness:InvalidArgumentInputs, flags, dimensions, or options are malformed.descriptive statistics: invalid argument
RunMat:skewness:InternalInternal tensor conversion or allocation fails.descriptive statistics: internal error

How skewness works

  • Flag 1 is the default biased moment estimator.
  • Flag 0 applies the usual finite-sample bias correction and returns NaN for slices with fewer than three values.
  • Slices with zero variance return NaN.
  • NaNs are treated as missing and omitted from each slice by default.

Example

Skewness across all values

s = skewness(x, 0, "all")

Using skewness with coding agents

Open a RunMat example with live inputs, then ask the agent to explain how skewness changes the result.

Run a small skewness example, explain the result, then change one input and compare the output.

FAQ

What is the default flag?

The default is 1, the biased moment estimator used by MATLAB.

Open-source implementation

Unlike proprietary runtimes, every RunMat function is open-source. Read exactly how skewness is executed, line by line, in Rust.

About RunMat

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