"...an interesting book, certainly controversial in some respects for scholars in the field. It has a strong data analytic focus and requires some background in multivariate analysis and biplot theory for a good understanding. It overemphasizes links to correspondence analysis at times, but is Very well written and didactically nicely sliced ​​into modules numbering exactly eight pages each. Most examples in the book are reproducible in the R environment. Finally, it will help the analyst to reflect on the use of weights, to the benefit of the analysis of compositional Data."
―Jan Graffelman in the Biometrical Journal , March 2019

The book takes a essential reference as a practical way to evaluate and interpret compositional data across a broad spectrum of disciplines in the life and natural sciences for both academia and industry. The book takes a prescribed approach starting with the definition of compositional data, the Use Of logratios for dimension reduction, clustering and variable selection issues along with several practical examples and a case study. The theory of compositional data analysis and computational aspects are

included as Appendices.

This book can be used at the undergraduate level as part of a course in data analysis. At the graduate level, for research studies, this book is essential in understanding how to collect and interpret compositional data. Using the methods described in this book will help To avoid costly mistakes made from misinterpreting compositional data."
―Professor Eric Grunsky, Department of Earth and Environmental Sciences, University of Waterloo Waterloo, Ontario, Canada  

"Clearly the best introduction to compositional data analysis"
―Professor John Bacon-Shone

About the Author

Michael Greenacre  is Professor of Statistics at the Universitat Pompeu Fabra, Barcelona, ​​Spain, where he teaches a course, amongst others, on Data Visualization. He has authored and co-edited nine books and 80 journal articles and book chapters, mostly on correspondence analysis , the latest being Correspondence Analysis in Practice (Third Edition) in 2016. He has given short courses in fifteen countries to environmental scientists, sociologists, data scientists and marketing professionals, and has specialized in statistics in ecology and social science