Abstract

Abstract: Compositional data are those which contain only relative information. They are parts of some whole. In most cases they are recorded as closed data, i.e. data summing to a constant, such as 100 %- whole-rock geochemical data being classic examples. Compositional data have important and particular properties hat preclude the application f standard statistical techniques on such data in raw form. Standard techniques are designed to be used with data that are free to range from-oo to +oo. Compositional data are always positive and range only from 0 to 100, or any other constant, when given in closed form. If one component increases, others must, perforce, decrease, whether or not there is a genetic link between these components. This means that the results of standard statistical analysis of the relationships between raw components orparts in a compositional dataset are clouded by spurious effects. Although such analyses may give appar-ently interpretable r sults, they are, at best, approximations and need to be treated with consider-able circumspection. The methods outlined in this volume are based on the premise that it is the relative variation of components which s of interest, rather than absolute variation. Log-ratios of components provide the natural means of studying compositional data. In this contribution the basic terms and operations are introduced using simple numerical examples to illustrate their com-