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

The following example employs multivariate analysis of variance (MANOVA) to measure differences in the chemical characteristics of ancient pottery found at four kiln sites in Great Britain. The data ...

Course TopicsMultivariate 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 ...

This distance is plotted as a time trend and control limits are applied to help engineers find abnormal data. Case study: Multivariate monitoring for manufacturers Here is a real-world example of ...

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

Multivariate analysis techniques may be used for several purposes, such as dimension reduction, clustering, or classification. The primary goal of this short course is to help researchers who want to ...

Instead, we develop a multivariate model for ordinal trait analysis and implement an EM algorithm for parameter estimation. We also propose a method for calculating the variance-covariance matrix ...

A common objective in exploratory multivariate analysis is to identify a subset of the variables which conveys the main features of the whole sample. Analysis of a well-known multivariate data set ...

Multivariate Exploratory Analysis of Ordinal Data in Ecology: Pitfalls, Problems and Solutions, Journal of Vegetation Science, Vol. 16, No. 5 (Oct., 2005), pp. 497-510 ...