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A Primer Of Ecological Statistics 1st Edition

4.8 out of 5 stars 23 customer reviews
ISBN-13: 978-0878932696
ISBN-10: 0878932690
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Editorial Reviews

Review

In short, only positive superlatives come to mind to describe the merit of this book. Its obvious strength is that is was written by ecologists for ecologists. From now on, I will use this textbook to teach statistics to undergraduate students and I will suggest it to graduate students and researchers who need to refresh their statistical knowledge. --Marie-Josée Fortin, Écoscience

This volume provides a wonderful review of traditional statistical methods. It is also an introduction to new statistical ideas. I highly recommend it. --Philip M. Dixon, The Quarterly Review of Biology

This volume provides a wonderful review of traditional statistical methods. It is also an introduction to new statistical ideas. I highly recommend it. --Philip M. Dixon, The Quarterly Review of Biology

About the Author

Nicholas J. Gotelli is Professor in the Department of Biology at the University of Vermont. He graduated with a B.A. from the University of California, Berkeley in 1980, and earned his Ph.D. at Florida State University in 1985. He is also the author of A Primer of Ecology, third edition (2001, Sinauer Associates, Inc.), Null Models in Ecology (with Gary R. Graves; 1996, Smithsonian Press), and EcoSim, an ecological software package. Dr. Gotelli currently serves on the Board of Editors of Ecology and Ecology Letters. His research interests include: the evolutionary ecology of carnivorous plants, biogeography, null model analysis of community structure, ant diversity, and demography. Aaron M. Ellison is Senior Research Fellow in Organismic and Evolutionary Biology at the Harvard Forest, and Adjunct Professor in the Graduate Program in Organismic and Evolutionary Biology at the University of Massachusetts at Amherst. He received a B.A. in 1982 from Yale University, and a Ph.D. from Brown University in 1986. Dr. Ellison received the National Science Foundation's Presidential Faculty Fellow award in 1992 for 'demonstrated excellence and continued promise both in scientific and engineering research and in teaching future generations of students to extend and apply human knowledge.' His research foci include: food web dynamics, community ecology of wetlands and forests, evolutionary ecology of carnivorous plants, and the application of Bayesian inference to ecological research and environmental decision-making. Dr. Ellison currently serves as Associate Editor-in-Chief of Ecology and Ecological Monographs, with primary responsibility for statistically oriented manuscripts
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Product Details

  • Paperback: 492 pages
  • Publisher: Sinauer Associates; 1 edition (May 1, 2004)
  • Language: English
  • ISBN-10: 0878932690
  • ISBN-13: 978-0878932696
  • Product Dimensions: 0.5 x 7 x 9 inches
  • Shipping Weight: 1.8 pounds
  • Average Customer Review: 4.8 out of 5 stars  See all reviews (23 customer reviews)
  • Amazon Best Sellers Rank: #117,714 in Books (See Top 100 in Books)

Customer Reviews

Top Customer Reviews

By Michael Meredith on April 5, 2005
Format: Paperback
I was delighted with this book, because it fits some of my own prejudices about statistics!

We agree that the mechanics of statistical analysis are not the most important part of statistics for ecological studies. After all, for the last couple of decades the brunt of this has been borne by computers and software engineers. Much more important is that researchers understand what the computer output means. And Gotelli and Ellison devote most of their book to this.

Too many people collect data, then try to work out how to analyse it and what conclusions to draw. It's better to decide on the research question right at the start, then decide what kind of analysis is appropriate, and then what numbers you need to collect. The main part of this book is about this study design process.

In addition to the conventional frequentist approach, the book introduces Monte Carlo methods and Bayesian thinking. (I was interested to see that they reject non-parametric methods out of hand, recommending the use of Monte Carlo methods instead.) Moreover, they deal with parameter estimation and model building as well as hypothesis testing.

Written by ecologists for ecologists, it is remarkably clear and easy to read. You don't need much math to be able to follow the arguments, and numerical examples are there. (I for one can't cope with too much algebra; I need to see some numbers slotted in and results come out.) The final chapter is an exception, as it uses matrix algebra, but there's enough explanation of this in an appendix. Remember that the number crunching will be done by your statistical package: it will probably do things right if you ask it to do the right things, and this book is a guide to the right things to do with your data.
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I have found this treatment of statistics unusually lucid and practical for the ecologist (or, I imagine, other scientist) desiring a better understanding of statistics and guidance in practical use of various types of statistical analysis. Unlike many statistical texts, it takes an almost conversational tone in explaining many concepts, using clear examples to illustrate various statistical approaches. While it is not as complete or detailed as larger statistical texts, it covers the fundamentals of most of the important tests and methods ecologists use on a day-to-day basis. One area of weakness is the treatment of classical non-parametric analyses, which Gotelli trades in entirely for Bayesian or Monte Carlo methods.

All in all, a very useful book for an aspiring ecologist to have on his or her bookshelf.
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I'm a biologist and a writer. I am not a mathematician. This book presents a broad array of statistical concepts in a way that even I can understand. You won't have to reread paragraph after paragraph, because the text is completely straightforward. Don't expect to use this as your stand-alone statistics reference, but do expect to use it as a primary source for ecology-related techniques. A "must have" for all biologists.
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For all you ecology and nature types, this is the stats textbook for you. These guys explain all the important stats concepts using examples I understand, like ant hills and bird density, and they cite real life experiments, give real experimental design suggestions, etc. Never before have I understood complex statistical concepts as well as I do after reading this book. And it's enjoyable reading! They really have a sense of humor. It's a must-have for everyone doing research in the fields of ecology or wildlife science!
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While the preface and first chapter of this book do a good job of simply explaining the terms used in statistics, I find that the authors needed to spend more time fleshing out the concepts. I've been looking for a statistics book that focuses on ecology and the environment, and I believe this one can be it; I would like to have seen different scenarios used in the examples, rather than one scenario, then a rapid shuffle forward to the next example. A good one to add to a statistics course, or to discuss in a class setting...or even with someone who knows statistics inside-out.
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While one may have to be in an optimal state of mind before sitting down with this book, it is definitely worth the time going through the different quantitative and experimental methods that ecologists use in evaluating the biosphere for those who will need such tools in going about their field work.
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This book was required for an introductory stats class that I took. With no background in statistics, I had trouble using this book. While the information in the book was good, I needed a beginners book that had practice problems and clear concepts. I give the book a five star and the professor a 1 star.
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A great book which explains, in 'understandable' detail, the statistical tests used for understanding the world around us. It describes each test, how it works (mathematically), when it can/can't-should/shouldn't be used, its weaknesses, alternative tests, and so on. It's so easy a cave man can do it! I wish I had this book before I started my graduate education at Auburn University. (MS, Fishery Science).

Seriously, it make statistics much easier to understand. I took Experimental stats 1 and 2 at Auburn, they were good classes, but this book is just so good.

It's an absolute MUST-HAVE for any aspiring biologist. You can't be a biologist without coming to terms with stats.
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