Visualization and Verbalization of Data

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.

Table of Contents

Chapter 1: Some Prehistory of CARME: Visual Language and Visual Thinking
Chapter 2: Some History of Algebraic Canonical Forms and Data Analysis
Chapter 3: Historical Elements of Correspondence Analysis and Multiple Correspondence Analysis
Chapter 4: History of Nonlinear Principal Component Analysis
Chapter 5: History of Canonical Correspondence Analysis
Chapter 6: History of Multiway Component Analysis and Three-Way Correspondence Analysis
Chapter 7: Past, Present, and Future of Multidimensional Scaling
Chapter 8: History of Cluster Analysis
Chapter 9: Simple Correspondence Analysis
Chapter 10: Distributional Equivalence and Linguistics
Chapter 11: Multiple Correspondence Analysis
Chapter 12: Structured Data Analysis
Chapter 13: Empirical Construction of Bourdieu’s Social Space
Chapter 14: Multiple Factor Analysis:General Presentation and Comparison with STATIS
Chapter 15: Data Doubling and Fuzzy Coding
Chapter 16: Symbolic Data Analysis: A Factorial Approach Based on Fuzzy Coded Data
Chapter 17: Group Average Linkage Compared to Ward’s Method in Hierarchical Clustering
Chapter 18: Analysing a Pair of Tables: Coinertia Analysis and Duality Diagrams