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 ...

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 ...

Discover how multivariate models use multiple variables for investment forecasting, risk analysis, and decision-making in ...

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

Combination of everolimus with R-CHOP (ever R-CHOP) as an initial therapy for diffuse large B-cell lymphoma (DLBCL): A phase I and feasibility study (NCCTG N1085 [Alliance]). Multivariate analyses of ...

This course is available on the MPhil/PhD in Environmental Economics, MPhil/PhD in International Relations, MPhil/PhD in International Relations, MPhil/PhD in Social Policy, MPhil/PhD in Social ...

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

Agglomerative-polythetic methods (commonly known as `similarity methods') of hierarchically classifying elements into sets can take a large number of different forms, according to: (a) the type of ...