Visualization and Verbalization of Data Chapman & Hall/CRC Computer Science & Data Analysis Series

Visualization and Verbalization of Data shows how correspondence analysis and related techniques enable the display of data in graphical form, which results in the verbalization of the structures in data. Renowned researchers in the field trace the history of these techniques and cover their current applications.

The first part of the book explains the historical origins of correspondence analysis and associated methods. The second part concentrates on the contributions made by the school of Jean-Paul Benzécri and related movements, such as social space and geometric data analysis. Although these topics are viewed from a French perspective, the book makes them understandable to an international audience.

Throughout the text, well-known experts illustrate the use of the methods in practice. Examples include the spatial visualization of multivariate data, cluster analysis in computer science, the transformation of a textual data set into numerical data, the use of quantitative and qualitative variables in multiple factor analysis, different possibilities of recoding data prior to visualization, and the application of duality diagram theory to the analysis of a contingency table.

History of Correspondence Analysis and Related Methods: Some Prehistory of CARME: Visual Language and Visual Thinking. Some History of Algebraic Canonical Forms and Data Analysis. Historical Elements of Correspondence Analysis and Multiple Correspondence Analysis. History of Nonlinear Principal Component Analysis. History of Canonical Correspondence Analysis. History of Multiway Component Analysis and Three-Way Correspondence Analysis. Past, Present, and Future of Multidimensional Scaling. History of Cluster Analysis. The Contribution of Benzécri and the French School: Simple Correspondence Analysis. Distributional Equivalence and Linguistics. Multiple Correspondence Analysis. Structured Data Analysis. Empirical Construction of Bourdieu’s Social Space. Multiple Factor Analysis: General Presentation and Comparison with Statis. Data Doubling and Fuzzy Coding. Symbolic Data Analysis: A Factorial Approach Based on Fuzzy Coded Data. Group Average Linkage Compared to Ward’s Method in Hierarchical Clustering. Analyzing a Pair of Tables: Co-Inertia Analysis and Duality Diagrams. References.