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Applying statistical concepts to biological scenarios, this established textbook continues to be the go-to tool for advanced undergraduates and postgraduates studying biostatistics or experimental design in biology-related areas. Chapters cover linear models, common regression and ANOVA methods, mixed effects models, model selection, and multivariate methods used by biologists, requiring only introductory statistics and basic mathematics. Demystifying statistical concepts with clear, jargon-free explanations, this new edition takes a holistic approach to help students understand the relationship between statistics and experimental design. Each chapter contains further-reading recommendations, and worked examples from today's biological literature. All examples reflect modern settings, methodology and equipment, representing a wide range of biological research areas. These are supported by hands-on online resources including real-world data sets, full R code to help repeat analyses for all worked examples, and additional review questions and exercises for each chapter.
List of Acronyms
Preface
1. Introduction
2. Things to Know Before Proceeding
3. Sampling and Experimental Design
4. Introduction to Linear Models
5. Exploratory Data Analysis
6. Simple Linear Models with One Predictor
7. Linear Models for Crossed (Factorial) Designs
8. Multiple Regression Models
9. Predictor Importance and Model Selection in Multiple Regression Models
10. Random Factors in Factorial and Nested Designs
11. Split-plot (Split-unit) Designs: Partly Nested Models
12. Repeated Measures Designs
13. Generalized Linear Models for Categorical Responses
14. Introduction to Multivariate Analyses
15. Multivariate Analyses Based on Eigenanalyses
16. Multivariate Analyses Based on (dis)similarities or Distances
17. Telling Stories with Data
References
Glossary
Index
Gerry Quinn is an Honorary Professor in the School of Life and Environmental Sciences at Deakin University, having served as Chair of Marine Biology and Head of Warrnambool Campus during his academic career. He has extensive experience in teaching biostatistics at Deakin University and the University of Gothenburg.
Michael J. Keough is an ecologist, environmental scientist, and Professor in the School of Biosciences at the University of Melbourne. He has taught classes in ecology, experimental design, and environmental science for many years at the University of Melbourne and in the US.
Reviews of the first edition:
"At last, a book that provides a readable introduction to nuances of statistical methods and analysis [...] a wonderful book that is packed with lots of practical advice [...]"
– Journal of Experimental Marine Biology and Ecology
"[...] this is clearly written text with a simple no-nonsense approach to the topic."
– TEG News
"[...] the book is well written and well presented with a good range of interesting and realistic examples [...] the book gave a very substantial and worthwhile study of good statistical practice in the design and analysis of biological experiments. I recommend it to anyone involved in quantitative biological research."
– Journal of Agricultural Science
"Quinn and Keough make plenty of reference to the recent and primary statistical literature, yet their book does not seem inaccessible or daunting [...] the text often ventures into statically uncertain territory, and Quinn and Keough do an excellent job of evenhandedly summarizing any statistical debates and philosophies then giving pragmatic suggestions to how best to proceed with analyses. Readers will find themselves adequately and interestedly informed [...] Quinn and Keough make extensive use of data sets deriving from real, and recently published, studies [...] There are also unexpected bonus sections, such as the useful, and at times fun, chapter on presenting the results of analysis both in reports and in seminars. In general, one certainly has the impression that the authors set out to write a clear, comprehensive and valuable book: they have succeeded."
– Animal Behaviour
"[...] highly recommended [...]"
– Ethology
"[...] the authors do go a long way towards success in their aim of encouraging 'readers to understand the models underlying the most common experimental designs' and to approach proper data analysis with more confidence. The web support is also very useful especially for items that the authors added post-publication [...]"
– Primate Eye
"[...] an essential textbook that can be warmly recommended to any student or researcher in biology who needs to design experiments, devise sampling programs and analyze the resulting data [...] There is a wealth of information that is usually only found in separate sources."
– Basic and Applied Ecology
"[...] an essential textbook for students and researchers in biology needing to design experiments, sampling programs or analyze the resulting data."
– Folia Geobotanica
