The past as ecological prelude

be able to apply mathematics and the models to be an effective data analyst, one also has to acquire a feel for data and how it interacts with the models, and there is a lot of statistical lore to help. Earl McCoy’s chapter in the book provides a good discussion of the ecological aspects of this messiness, but in general statistical messiness is underrepresented in this book. Despite my misgivings, there is still a lot to be gained from reading this book. It provides some decent overviews of different contemporary methods and models that can be used by ecologists who want to analyse their own (or other ecologists’) data. But where it (like, in fairness, many other statistics books) falls short is in helping ecologists understand their experiment and data in the way that a statistician would. This book will be helpful for ecologists wanting to apply statistics to their data, but if they want to understand what they are doing, they might have to wait for the play to come.