Analyzing Compositional Data with R Introduction Fundamental Concepts of Compositional Data Analysis Distributions for Random Compositions Descriptive Analysis of Compositional Data Linear Models for Compositions Multivariate Statistics Zeroes Missings and Outliers References Index. . This book presents the statistical analysis of compositional data sets i.e. data in percentages proportions concentrations etc. The subject is covered from its grounding principles to the practical use in descriptive exploratory analysis robust linear models and advanced multivariate statistical methods including zeros and missing values and paying special attention to data visualization and model display issues. Many illustrated examples and code chunks guide the reader into their modeling and interpretation. And though the book primarily serves as a reference guide for the R package “compositions ” it is also a general introductory text on Compositional Data Analysis. Awareness of their special characteristics spread in the Geosciences in the early sixties but a strategy for properly dealing with them was not available until the works of Aitchison in the eighties. Since then research has expanded our understanding of their theoretical principles and the potentials and limitations of their interpretation. This is the first comprehensive textbook addressing these issues as well as their practical implications with regard to software. The book is intended for scientists interested in statistically analyzing their compositional data. The subject enjoys relatively broad awareness in the geosciences and environmental sciences but the spectrum of recent applications also covers areas like medicine official statistics and economics. Readers should be familiar with basic univariate and multivariate statistics. Knowledge of R is recommended but not required as the book is self contained.