Experimental Design and Data Analysis for BiologistsPaperback
List price $77.70
You save $12.45 16% off
Free delivery worldwide
Dispatched in 3 business days
When will my order arrive?
- Publisher: CAMBRIDGE UNIVERSITY PRESS
- Format: Paperback | 553 pages
- Dimensions: 190mm x 244mm x 28mm | 1,338g
- Publication date: 1 April 2002
- Publication City/Country: Cambridge
- ISBN 10: 0521009766
- ISBN 13: 9780521009768
- Illustrations note: 125 b/w illus. 85 tables
- Sales rank: 39,584
An essential textbook for any student or researcher in biology needing to design experiments, sample 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 website that provides all data sets, questions for each chapter and links to software.
Other people who viewed this bought:
USD$70.50 - Save $3.33 (4%) - RRP $73.83
USD$59.50 - Save $2.66 (4%) - RRP $62.16
USD$89.31 - Save $11.70 11% off - RRP $101.01
Other books in this category
USD$13.37 - Save $0.60 (4%) - RRP $13.97
USD$12.82 - Save $5.18 28% off - RRP $18.00
USD$13.32 - Save $9.98 42% off - RRP $23.30
USD$23.63 - Save $7.46 23% off - RRP $31.09
USD$11.95 - Save $5.13 30% off - RRP $17.08
USD$21.64 - Save $3.21 12% off - RRP $24.85
Gerry Quinn is a Senior Lecturer in the School of Biological Sciences at Monash University, and Program Leader in the Cooperative Research Centre for Freshwater Ecology. He has taught experimental design and analysis courses for a number of years and has provided advice on the design and analysis of sampling and experimental programs in ecology and environmental monitoring to a wide range of university and government scientists. Gerry Quinn is a co-author of Monitoring Ecological Impacts: Concepts and Practice in Flowing Waters, Cambridge University Press, 2002. Michael Keough is a Reader in Zoology at the University of Melbourne. His research interests lie in marine ecology, environmental science, and conservation biology. He has extensive experience teaching experimental design and analysis courses at a number of universities. He has also provided advice on design and analysis for environmental monitoring to a wide range of environmental consultants, and state and federal governments in Australia. Michael Keough is a co-author of Monitoring Ecological Impacts: Concepts and Practice in Flowing Waters, Cambridge University Press, 2002.
'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
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.