This richly illustrated book describes the use of interactive and dynamic graphics as part of multidimensional data analysis. Chapters include clustering, supervised classification, and working with missing values. A variety of plots and interaction methods are used in each analysis, often starting with brushing linked low-dimensional views and working up to manual manipulation of tours of several variables. The role of graphical methods is shown at each step of the analysis, not only in the early exploratory phase, but in the later stages, too, when comparing and evaluating models. All examples are based on freely available software: Ggobi for interactive graphics and R for static graphics, modeling, and programming. The book may be used as a text in a class on statistical graphics or exploratory data analysis, for example, or as a guide for the independent learner. Each chapter ends with a set of exercises.

The book's examples use the software R and GGobi Illustrated examples, supplemented by movies on the web, help he reader learn how to use interactive graphics for data anlaysis Full color figures illuminate high-dimensional data spaces Everything in the book can be replicated by the reader with free software Request lecturer material: sn.pub/lecturer-material

Inhalt
TheToolbox.- Missing Values.- Supervised Classification.- Cluster Analysis.- Miscellaneous Topics.- Datasets.