Experimental Design and Data Analysis for Biologists

by Michael J. Keough and Gerry P. Quinn

Book Overview

This essential textbook is designed for students or researchers in biology who need to design experiments, sampling programs, or analyze resulting data. The text begins with a revision of estimation and hypothesis testing methods, before advancing to the analysis of linear and generalized linear models. The chapters include such topics as linear and logistic regression, simple and complex ANOVA models, log-linear models, and multivariate techniques...

• Format: Paperback
• Language: English
• ISBN: 0521009766
• ISBN13: 9780521009768
• Release Date: April 2002
• Publisher: Cambridge University Press
• Length: 553 Pages
• Weight: 2.60 lbs.
• Dimensions: 1.2" x 7.4" x 9.6"

Customer Reviews

Good introductory text

This text is a well-written compliment to the more traditional stats texts such as Zar, Sokal, etc. It provides excellent examples using real data sets as well as literature references and analysis issues and hints in the end of chapter summaries. The index is poorly organized and there could be a more definitive glossary to go along with the text. Overall, I enjoyed using this text and delving into the references as part of a lifelong effort to utilize biostatistics!

A solid resource for research scientists

I've found this book to be a valuable resource for less common methods of experimental design. Its biggest strength is the ubiquitous use of examples from real research papers.

Finally something that makes sense!!

I have finally found a useable experimental design book. This book is as it's titled is for biologists and it is understandable. This book could have saved me from the frustration of 'not knowing' the proper terminology in project design. There is a easier, concise way to say something about 'what I wanted to do in the field.' I am finally satisfied in my quest for an understandable design and data analysis book! I would have liked to have had the information this text has before I had to jump into writing proposals - even if the proposals were only for course work. (I have recommended this book to my professor to use in future courses and to fellow grad students.) I highly recommend this book!! A second choice would be "Vegetation Description and Data Analysis: A Practical Approach" by Kent and Coker. These books combined have made my project design understandable. (The latter is a bit harder to find - I had mine shipped over from India) Again can't recommend this one enough - Thank you so much G. P. Quinn!!

Designing your field studies

The book is riddled with different examples from articles of recent and past publications which have both good and bad experimental designs. The authors tried to explain the basic underlying designs of these published field studies and then they tried to give suggestions of how it would have been to be without underestimating the cost and labor done by the published authors.Most of the examples come from field community ecology, and I think this book is highly recommended for aspiring field ecologist as the numerous examples cited can guide you to design against what is superficial, unprepared field experiments. Not to limit the book, this works also even for other fields in biology such as laboratory studies. The principles being taught can be applied in both.

Comprehensive, advanced, and often a good read

Comprehensible, comprehensive, and interesting statistical texts are as rare as the Tasmanian Tiger. This text is very comprehensive and is loaded with interesting examples and does an excellent job of presenting the scientific method. It's not always as easy to follow as I would like, but I deal with this by recommending to my students that they read the assignment after, instead of before the lecture. I cover the first 12 chapters (through covariance) in my upper division Biometry course. I'm an ecologist and have enjoyed learning much that was never covered in my undergraduate biometry and two graduate statistics courses. This would be an excellent text for graduate courses.