Multivariate statistics
Multivariate statistics is a subdivision of statistics encompassing the simultaneous observation and analysis of more than one outcome variable. The application of multivariate statistics is multivariate analysis.
Pronunciation
- Multivariate: /ˌmʌltɪˈveəriət/
- Statistics: /stəˈtɪstɪks/
Etymology
The term "multivariate statistics" is derived from the Latin "multi-" meaning "many", and "variates" which refers to the different outcomes that are being observed.
Definition
Multivariate statistics is a form of statistics involving the simultaneous observation and analysis of more than one statistical outcome variable at a time. In design and analysis, the technique is used to perform trade studies across multiple dimensions while taking into account the effects of all variables on the responses of interest.
Related Terms
- Univariate statistics: The simplest form of statistical analysis, dealing with observations on only one variable at a time.
- Bivariate statistics: This involves the statistical analysis of exactly two variables.
- Multivariate analysis: This is a set of techniques used for analysis of data that contain more than one variable, and the techniques are especially valuable when working with correlated variables.
- Correlation: A statistical measure that expresses the extent to which two variables are linearly related.
- Regression analysis: A set of statistical processes for estimating the relationships among variables.
Applications
Multivariate statistics are used in many disciplines, including biostatistics, econometrics, machine learning, psychometrics, marketing, sociology, and agricultural science. They are used to understand the structure of the data, to test hypotheses, and to form predictions.
See Also
- Principal component analysis
- Factor analysis
- Canonical correlation
- Cluster analysis
- Discriminant function analysis
External links
- Medical encyclopedia article on Multivariate statistics
- Wikipedia's article - Multivariate statistics
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