MultivariateMeanDeviation[matrix]
gives the mean of the Euclidean distances between the elements of matrix and their mean.


MultivariateMeanDeviation
MultivariateMeanDeviation[matrix]
gives the mean of the Euclidean distances between the elements of matrix and their mean.
Details and Options
- To use MultivariateMeanDeviation, you first need to load the Multivariate Statistics Package using Needs["MultivariateStatistics`"].
- MultivariateMeanDeviation is a univariate measure of mean deviation for multivariate data.
- The multivariate mean deviation is given by
∑iNorm[xi-
], where matrix={x1,x2,…,xn} and
=Mean[matrix].
- MultivariateMeanDeviation handles both numerical and symbolic data.
See Also
Tech Notes
Related Guides
Text
Wolfram Research (2007), MultivariateMeanDeviation, Wolfram Language function, https://reference.wolfram.com/language/MultivariateStatistics/ref/MultivariateMeanDeviation.html.
CMS
Wolfram Language. 2007. "MultivariateMeanDeviation." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/MultivariateStatistics/ref/MultivariateMeanDeviation.html.
APA
Wolfram Language. (2007). MultivariateMeanDeviation. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/MultivariateStatistics/ref/MultivariateMeanDeviation.html
BibTeX
@misc{reference.wolfram_2025_multivariatemeandeviation, author="Wolfram Research", title="{MultivariateMeanDeviation}", year="2007", howpublished="\url{https://reference.wolfram.com/language/MultivariateStatistics/ref/MultivariateMeanDeviation.html}", note=[Accessed: 13-August-2025]}
BibLaTeX
@online{reference.wolfram_2025_multivariatemeandeviation, organization={Wolfram Research}, title={MultivariateMeanDeviation}, year={2007}, url={https://reference.wolfram.com/language/MultivariateStatistics/ref/MultivariateMeanDeviation.html}, note=[Accessed: 13-August-2025]}