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 ...

Larry Hatcher, Ph.D. and Edward J. Stepanski, Ph.D. Introduction: The Basics of One-Way ANOVA, Between-Groups Design Example with Significant Differences between Experimental Conditions Understanding ...

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

In semiconductor manufacturing, especially in electrical test data, but also in other parameters, there are often sets of parameters that are very highly correlated. Even a change in the correlation ...

where L is a linear function on the regressor side, is a matrix of parameters, c is a column vector of constants, j is a row vector of ones, and M is a linear function on the dependent side. The ...

Cristani, C. and Tessera, D. (2026) A Foundational Protocol for Reproducible Visualization in Multivariate Quantum Data. Open Access Library Journal, 13, 1-13. doi: 10.4236/oalib.1114704 .

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 ...

3 Produce visualisations of multivariate data using principal components analysis (PCA) and non-metric multi-dimensional scaling (MDS) using statistical software. 4 Perform analyses to relate two sets ...