'The new edition of this 'go-to' text, has been revised to take a more holistic, informative, and up-to-date approach to the subject. This remarkably accessible, practical and - at times - entertaining guide to how we can best translate our questions and ideas into informative experiments and analyses is highly recommended for everyone wanting to investigate, visualise, and analyse biological phenomena.' Jonathon Havenhand, University of Gothenburg
'The new book is an excellent resource for researchers, analysts and teachers. The text clearly outlines the important concepts of the tests and models. The examples are all based on published data which makes it easy to source the full manuscript, datasets and replicate the analyses which is incredibly important and assists with interpretation.' Victoria Goodall, VLG Statistical Services
'At last, a book for undergraduates and graduates that distills the complexities of biological data analysis into an easy-to-understand generalized linear model approach - with examples in R! The authors challenge the reader to think critically about data by providing important details on design, summary statistics, power analysis/effect size, model fit, and data visualization. This book will be used in my classes for years to come.' Greg Moyer, Mansfield University
'I have been using Experimental Design and Data Analysis for teaching and research for 20 years and have been hoping for a second edition for 10. It was worth the wait. The new edition shares many attributes with the original. It is quite easy to read, the examples are varied and interesting, there are ample and revealing box examples and there remains an attitude of Statistics as a tool that will be used by many. There are a number of changes that reflect these attributes - two key ones are the emphasis on Generalized Models as a framework for a broad array of approaches and the conversion of examples to R, with code and additional material available online.' Peter Raimondi, University of California, Santa Cruz
'I have taught in and coordinated a third-year design/statistics paper for zoology and ecology students for ten years - an enjoyable and sometimes challenging task. The first edition of Quinn and Keough has been immensely helpful for me in teaching this course. The second edition has been updated and expanded considerably. I'm sure it will continue to inspire my future teaching.' Christoph Matthaei, University of Otago
'I was excited to see Quinn and Keough have updated their classic guide to experimental design and data analysis. I read the earlier edition of this book as a graduate student, and the advice it provides on experimental design is the foundation of my own studies, as well as my approach to training graduate students ... This book is foundational reading for aspiring scientists. Not only does it teach you how to analyse your data, it also provides invaluable advice on how to communicate analyses and write up scientific studies. The book's advice will help give early career scientists the confidence they need to write-up and publish their first studies.' Chris Brown, University of Tasmania
