Visualization and Verbalization of Data

Jorg Blasius, Michael Greenacre

"This book presents a set of techniques for data analysis, together with the history of how these methods were developed. The audience seems to be those who are interested in these techniques, or, invested already in them, are curious about the history and intellectual process that led to their development… VAVOD [Visualization and Verbalization of Data] is a worthwhile read. Many of the chapters can be used as stand-alone introductions to particular techniques, including both theory and applications; as a collection, they offer a somewhat uneven but wide ranging and far reaching overview of a vibrant field of intellectual activity. The fact that many of the chapters are written by founders of the field, writing about techniques they created, refined and developed over decades, lends this book unusual gravitas as both a work of reference and as a document."—Omar De la Cruz Cabrera, Kent State University, in The American Statistician, August 2016"Given the continuing digitization of all facets of modern societies, we are fed with rapidly growing masses of data. At this pace, visualization is one decisive step to go beyond the factual knowledge of distributions to the recognition of conceptual spaces by advanced analytic methods. The big challenge will continue to be the verbalization of what we see as results of the analyses. This book lays the ground for significant advances on the way forward."—From the Foreword by Ekkehard Mochmann, Cologne

• 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.