Multivariate analysis is commonly used when we have more than one outcome variables for each observation. For instance, a survey of American adults’ physical and mental health might measure each ...

Multivariate count data arise in settings where two or more non‐negative integer outcomes are observed jointly. Such data feature prominently in fields as diverse as ecology (species abundances across ...

Statistics are often viewed as confusing and complicated, but multivariate data analysis (MVA) methods can be used to amass knowledge simply. Traditionally, studies are performed and analysed ...

Before we learn how to perform multivariate regression in Excel, it is important to have a refresher on regression as a whole and multivariate regression in particular. One of the hallmarks of human ...

Multivariate data analysis (MVDA) is being used to effectively handle complex datasets generated by process analytical technology (PAT) in biopharmaceutical process development and manufacturing.

A depth-based method allows ordering multivariate datasets, enabling valuable analysis methods to everything from bacteria movement to stock trades.

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A volume in the Chapman and Hall/CRC Statistics in the Social and Behavioural Sciences series. A copy of the book may be ordered from CRC Press (ISBN 13: 978-1584889601). Please use 20% discount code ...

Multivariate analysis in statistics is a set of useful methods for analyzing data when there are more than one variables under consideration. Multivariate analysis techniques may be used for several ...