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.
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Book Description
Editorial Reviews
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"This massive books fills an important niche: a reference book on advanced statistical methods for research biologists...It's impressive because it is totally new...Even more interesting is the fact that the data are actually available free for downloading from a website...there is so much packed into this book that I view it more as a reference than a textbook...it is wonderful and loaded with all the newest methods. I recommend it to readers who venture into more advanced statistics." Natural Areas Journal
"...it is evident that a great deal of scholarship has gone into this book and that there is much good advice in it." Ecology
"... the book is highly recommended. It provides a broad and in-depth overview over most of the commonly used statistical methods." Ethology
"...it is evident that a great deal of scholarship has gone into this book and that there is much good advice in it." Ecology
"... the book is highly recommended. It provides a broad and in-depth overview over most of the commonly used statistical methods." Ethology
Book Description
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.
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Most Helpful Customer Reviews
18 of 18 people found the following review helpful:
5.0 out of 5 stars
Comprehensive, advanced, and often a good read,
By
This review is from: Experimental Design and Data Analysis for Biologists (Paperback)
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.
4 of 4 people found the following review helpful:
5.0 out of 5 stars
Designing your field studies,
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This review is from: Experimental Design and Data Analysis for Biologists (Paperback)
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.
2 of 2 people found the following review helpful:
5.0 out of 5 stars
Finally something that makes sense!!,
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Amazon Verified Purchase(What's this?)
This review is from: Experimental Design and Data Analysis for Biologists (Paperback)
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!!
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Inside This Book
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First Sentence:
Biologists and environmental scientists today must contend with the demands of keeping up with their primary field of specialization, and at the same time ensuring that their set of professional tools is current. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
riparian tree density, cabin density, serpulid recruits, jth replicate observation, clump area, percentage shrub cover, suture width, ten chemical variables, unweighted marginal means, successional zone, net photosynthetic capacity, rank dissimilarities, unplanned pairwise comparisons, log expected frequency, added variance component, factor nested design, reciprocal averaging algorithm, unplanned multiple comparisons, crab biomass, new derived variables, partial regression slope, initial sample groups, five response variables, source canyon, marrow type Key Phrases - Capitalized Phrases (CAPs): (learn more)
Mac Nally, Catskill Mountains, Christmas Island, River Red Gum, Central Limit Theorem, North America, Coefficient Estimate Standard, Coefficient Standard, Eigenvalue Percentage, Residual Residual, Source Expected, Balboa Terrace, Delray Beach, Rocky Mountains, The Hosmer-Lemeshow, Gauging Station, Gulf of California, Standard Coefficient, Variable Component New!
Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Biologists and environmental scientists today must contend with the demands of keeping up with their primary field of specialization, and at the same time ensuring that their set of professional tools is current. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
riparian tree density, cabin density, serpulid recruits, jth replicate observation, clump area, percentage shrub cover, suture width, ten chemical variables, unweighted marginal means, successional zone, net photosynthetic capacity, rank dissimilarities, unplanned pairwise comparisons, log expected frequency, added variance component, factor nested design, reciprocal averaging algorithm, unplanned multiple comparisons, crab biomass, new derived variables, partial regression slope, initial sample groups, five response variables, source canyon, marrow type Key Phrases - Capitalized Phrases (CAPs): (learn more)
Mac Nally, Catskill Mountains, Christmas Island, River Red Gum, Central Limit Theorem, North America, Coefficient Estimate Standard, Coefficient Standard, Eigenvalue Percentage, Residual Residual, Source Expected, Balboa Terrace, Delray Beach, Rocky Mountains, The Hosmer-Lemeshow, Gauging Station, Gulf of California, Standard Coefficient, Variable Component New!
Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Citations (learn more)
This book cites 100
books:
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6
books
cite this book:
See all 6 books citing this book
- Applied Analysis of Variance in Behavioral Science (Statistics: A Series of Textbooks and Monographs) by Lynne Edwards on 9 pages
- Design and Analysis of Ecological Experiments by Samuel M. Scheiner on 6 pages
- Experimental Ecology: Issues and Perspectives by William J. Resetarits Jr. on 4 pages
- Advances in Biometry (Wiley Series in Probability and Statistics) by Peter Armitage on 4 pages
- Fundamentals of Exploratory Analysis of Variance (Wiley Series in Probability and Statistics) by David C. Hoaglin in Back Matter (1), Back Matter (2), and Back Matter (3)
See all 100 books this book cites
- Marine Biodiversity: Patterns and Processes, Assessment, Threats, Management and Conservation (Developments in Hydrobiology) by H. Queiroga on page 191, and page 227
- Total Maximum Daily Load: Approaches & Challenges by Tamim Younos on page 243, and page 249
- Monitoring Ecological Impacts: Concepts and Practice in Flowing Waters by Barbara J. Downes in Front Matter
- Plant Cell Biology by William V Dashek on page 15
- Bioassessment of Freshwater Ecosystems: Using the Reference Condition Approach by Robert Bailey in Back Matter
See all 6 books citing this book
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