An essential textbook for
any student or researcher in biology needing to design experiments, sampling programs or
analyse the resulting data. The text begins with a revision of estimation and hypothesis
testing methods, covering both classical and Bayesian philosophies, before advancing to
the analysis of linear and generalized linear models. Topics covered include linear and
logistic regression, simple and complex ANOVA models (for factorial, nested, block,
split-plot and repeated measures and covariance designs), and log-linear models.
Multivariate techniques, including classification and ordination, are then introduced.
Special emphasis is placed on checking assumptions, exploratory data analysis and
presentation of results. The main analyses are illustrated with many examples from
published papers and there is an extensive reference list to both the statistical and
biological literature. The book is supported by a web-site that provides all data sets,
questions for each chapter and links to software.
Table of Contents
1. Introduction; 2.
Estimation; 3. Hypothesis testing; 4. Graphical exploration of data; 5. Correlation and
regression; 6. Multiple regression and correlation; 7. Design and power analysis; 8.
Comparing groups or treatments - analysis of variance; 9. Multifactor analysis of
variance; 10. Randomized blocks and simple repeated measures: unreplicated two-factor
designs; 11. Split plot and repeated measures designs: partly nested anovas; 12. Analysis
of covariance; 13. Generalized linear models and logistic regression; 14. Analyzing
frequencies; 15. Introduction to multivariate analyses; 16. Multivariate analysis of
variance and discriminant analysis; 17. Principal components and correspondence analysis;
18. Multidimensional scaling and cluster analysis; 19. Presentation of results.
Reviews
'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
536 pages