MultivariateStatistics`
MultivariateStatistics`

# MultivariateSkewness

MultivariateSkewness[matrix]

gives a multivariate coefficient of skewness for matrix.

# Details and Options

• To use MultivariateSkewness, you first need to load the Multivariate Statistics Package using Needs["MultivariateStatistics`"].
• MultivariateSkewness is a univariate measure of skewness for multivariate data.
• MultivariateSkewness[matrix] is equivalent to where matrix={x1,x2,,xn}, Mean[matrix], and is the estimated population covariance matrix.
• A value of multivariate skewness close to zero indicates elliptical symmetry.

# Examples

## Basic Examples(1)

Multivariate skewness for bivariate data:

Wolfram Research (2007), MultivariateSkewness, Wolfram Language function, https://reference.wolfram.com/language/MultivariateStatistics/ref/MultivariateSkewness.html.

#### Text

Wolfram Research (2007), MultivariateSkewness, Wolfram Language function, https://reference.wolfram.com/language/MultivariateStatistics/ref/MultivariateSkewness.html.

#### CMS

Wolfram Language. 2007. "MultivariateSkewness." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/MultivariateStatistics/ref/MultivariateSkewness.html.

#### APA

Wolfram Language. (2007). MultivariateSkewness. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/MultivariateStatistics/ref/MultivariateSkewness.html

#### BibTeX

@misc{reference.wolfram_2024_multivariateskewness, author="Wolfram Research", title="{MultivariateSkewness}", year="2007", howpublished="\url{https://reference.wolfram.com/language/MultivariateStatistics/ref/MultivariateSkewness.html}", note=[Accessed: 25-July-2024 ]}

#### BibLaTeX

@online{reference.wolfram_2024_multivariateskewness, organization={Wolfram Research}, title={MultivariateSkewness}, year={2007}, url={https://reference.wolfram.com/language/MultivariateStatistics/ref/MultivariateSkewness.html}, note=[Accessed: 25-July-2024 ]}