This book presents details of the analysis of variance for a compendium of designs with up to three treatment factors. The book has a good discussion of practical situations where each design may be useful, ranging from the authors’ interests in ecology to more conventional examples from agricultural and medical research. It shows schematic plans of the type of data that will be collected, and the analysis of variance tables that should be generated. It also contains good advice about assumptions and interpretation of the analysis. It should thus be an invaluable reference for the target audience of post-graduate researchers. I do, however, have some concerns. The book requires considerable prior knowledge of design and analysis of variance, and has a tendency to use concepts before they are explained. Having a PhD in statistics I found this an interesting challenge, but a recent (non-statistical) MSc graduate soon became confused and discouraged. Nevertheless, the concepts are nearly all explained somewhere in the book, so persistence would be rewarded. More importantly, though, I am sceptical about the concept of a compendium of specific examples, and would have preferred to see more attention given to the underlying principles of design and anova, such as randomization, blocking and treatment structures. Readers would then be able to generalize the ideas, for example, to four-factor designs or to some of the omitted three-factor designs such as Latin squares with split plots. Nevertheless the book has many strengths and I am happy to recommend it.