Gerry P. Quinn

Experimental Design and Data Analysis for Biologists (eBook, ePUB)

• Format: ePub

Produktbeschreibung

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.

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Produktdetails

• Verlag: Cambridge University Press
• Erscheinungstermin: 21. März 2002
• Englisch
• ISBN-13: 9781107085664
• Artikelnr.: 52967366

Autorenporträt

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.

Inhaltsangabe

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.

Rezensionen

'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