Experimental Design and Data Analysis for Biologists
by Gerry P. Quinn, Michael J. Keough
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Book Summary Information
Author: Gerry P. Quinn, Michael J. KeoughEdition: Paperback
Published: 2002-04-02
ISBN: 0521009766
Number of pages: 520
Publisher: Cambridge University Press
Book Reviews of Experimental Design and Data Analysis for Biologists
Book Review: Finally something that makes sense!!
Summary: 5 Stars
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!!
Summary of Experimental Design and Data Analysis for Biologists
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. The main analyses are illustrated with many examples from published papers and an extensive reference list to both the statistical and biological literature is also included. The book is supported by a web-site that provides all data sets, questions for each chapter and links to software.An essential textbook for any student or researcher in biology needing to design experiments, sampling programs or analyse the resulting data. Both univariate and multivariate statistics are covered, and 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.
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.
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