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This book introduces the theory, methods, and applications of correspondence analysis. With an emphasis on data coding, it clearly demonstrates why this technique remains important and in the eyes of many, unsurpassed as an analysis framework. Within this highly practical presentation, the author provides a theoretical overview and software in Java and R for correspondence analysis, clustering, and interpretation tools. A full chapter of case studies explores a range of applications to time-evolving data and in areas such as financial modeling, shape analysis, and the biosciences. The software and all of the data sets used in the book are available on a supporting web site.