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 ...

Analyses of two-state phenotypic change are common in ecological research. Some examples include phenotypic changes due to phenotypic plasticity between two environments, changes due to ...

Multivariate analysis of cognitive tests in Alzheimer's disease identifies five distinct groups of Alzheimer's disease patients, and suggests that multivitamins might slow progression only in certain ...

This course is available on the MRes in Management (Marketing), MSc in Data Science, MSc in Health Data Science, MSc in Marketing, MSc in Statistics, MSc in Statistics (Financial Statistics), MSc in ...

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 ...

Our research group develops modern and efficient multivariate statistical methods tailored for different types of multivariate data, such as time series, spatial data, spatio-temporal data, or ...

Discriminant analysis was used to differentiate between experimental waste-flake assemblages resulting from different reduction strategies. The attributes used in the discriminant analysis consisted ...

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 ...