×

Warning

The RokSprocket Module needs the RokSprocket Component enabled.
Multivariate Methods

Multivariate Methods

Learn about multivariate methods and their insightful graphical data summaries. Discover popular and others less known, some classical as well as more recent ones with focus on real-life applications.

Learn about this data reduction technique to identify, quantify and visualise the correlation in set of measurements. PCA provides insightful data visualisation tools. Learn about innovative applications.

One of the oldest multivariate techniques, factor analysis is closely related to PCA and even confused by many for PCA. However, it serves a totally different purpose. Uncover hidden dimensions in your data.

Conceptually similar to PCA, correspondence analysis a method is designed for discovering associstions in categorical rather than continuous data. Discover the informative 2D-plots for efficient data mapping.

Learn how to take data (consumers, genes, stores, ...) and organise them into homogeneous groups for use in many applications, such as market analysis and biomedical data analysis, or as a pre-processing step for many data mining tasks. Cluster analysis comprises a collection of powerful techniques. Learn about this very active field of research in statistics and data mining, and discover new techniques.

The primary goal of this method is to discover which variables have the best ability of discriminating between two or more known groups in your data. Discrimimant analysis may also be used to build predictive analytics models.