Visualization And Verbalization Of Data (chapman & Hall/crc Computer Science & Data Analysis)

**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. Front Cover 1 Contents 10 Foreword 12 Preface 14 Editors 20 Contributors 22 Prologue: Let the Data Speak! 28 Chapter 1: Some Prehistory of CARME: Visual Language and Visual Thinking 46 Chapter 2: Some History of Algebraic Canonical Forms and Data Analysis 60 Chapter 3: Historical Elements of Correspondence Analysis and Multiple Correspondence Analysis 74 Chapter 4: History of Nonlinear Principal Component Analysis 88 Chapter 5: History of Canonical Correspondence Analysis 104 Chapter 6: History of Multiway Component Analysis and Three-Way Correspondence Analysis 120 Chapter 7: Past, Present, and Future of Multidimensional Scaling 138 Chapter 8: History of Cluster Analysis 160 Chapter 9: Simple Correspondence Analysis 180 Chapter 10: Distributional Equivalence and Linguistics 192 Chapter 11: Multiple Correspondence Analysis 208 Chapter 12: Structured Data Analysis 228 Chapter 13: Empirical Construction of Bourdieu’s Social Space 248 Chapter 14: Multiple Factor Analysis:General Presentation and Comparison with STATIS 266 Chapter 15: Data Doubling and Fuzzy Coding 282 Chapter 16: Symbolic Data Analysis: A Factorial Approach Based on Fuzzy Coded Data 298 Chapter 17: Group Average Linkage Compared to Ward’s Method in Hierarchical Clustering 314 Chapter 18: Analysing a Pair of Tables: Coinertia Analysis and Duality Diagrams 332 References 344 Back Cover 382 "This volume presents an overview of the state of the art in data visualization, encompassing correspondence analysis, nonlinear principal component analysis, cluster analysis, multidimensional scaling, and much more. It covers the historical development of each topic along with modern techniques and future research directions. To illustrate the methods, the book incorporates many real data examples and software implementations. Each chapter is written by leading researchers in the field and thoroughly edited to ensure coherence and consistency"-- Provided by publisher