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This concise book presents a very applied introduction to compositional data analysis, focussing on the use of R for analysis. It includes lots of real examples, code snippets, and colour figures, to illustrate the methods.

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As multiple correspondence analysis methods are capable of handling high-dimensional categorical data, they are applicable to survey research efforts in areas like the social sciences, marketing, health economics, and biomedicine. Using a practical approach, this book brings together the theory and applications of multiple correspondence analysis.

Correspondence Analysis in the Social Sciences gives a comprehensive description of this method of data visualization as well as numerous applications to a wide range of social science data. Various theoretical aspects are presented in a language accessible to both social scientists and statisticians and a wide variety of applications are given which demonstrate the versatility of the method to interpret tabular data in a unique graphical way.