Research methods suitable for the analysis of big datasets containing many variables. The fundamentals of data visualisation, customer segmentation, factor analysis and latent class analysis with ...

Symmetric wavelet frames represent a powerful class of mathematical tools designed for efficient and robust representation of high-dimensional data. They combine the inherent benefits of wavelet ...

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 ...

The Unscrambler® is a complete Multivariate Analysis and Experimental Design (DoE) software solution that is equipped with powerful methods, including PCA, Multivariate Curve Resolution (MCR), PLS ...

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 ...

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 ...

The new version has greatly improved performance and is optimized for even better usability, security and reliability. The Unscrambler® X version 10.2 continues CAMO’s tradition of delivering powerful ...

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 ...

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 ...