Customer Reviews

A Primer Of Ecological Statistics

5 star:		(15)
4 star:		(2)
3 star:		(1)
2 star:		(0)
1 star:		(0)

 

 

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.

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.

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.

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!

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.

I am using this book for my Master's in Environmental Science. Very useful tool that anyone going into scientific research should have! I will definitely keep this as a desk reference.

Used my advisor's copy to study for my preliminary exams. I loved it so much that now I am buying it. I agree with the reviewer who said this book is not for the beginner. That being said, there is a rich background of historical, philisophical, and practical points about statistics and how it applies to science that I just loved it. I recommend this book to any graduate student in an ecological field. If you need to bone up on your statistics and already forgot everything you learned in your clinical statistics class (because there weren't any ecological examples), this book is for you!

This text is very useful for understanding the theory behind statistics. It also attempts to help in decifering how to read statistical results. I wish I used it more before my first exam!

This is a GREAT book to be introduced to statistics applied to the environment and populations. It provides ready-to-use information for any kind of experimental design.
The title could even be misleading, because: (1) this is not a primer, it explains A LOT of analytical procedures and experiments (I never saw a primer explaining how and when to use a two-way ANOVA split-plot); (2) it could be a great reading also for people coming from different fields of study (from sociology to chemistry).

I bought this a few years ago because it was required for a field ecology course. Over time, it's proven to be the best statistics resource that I have - even better than the internet. My field is behavioral ecology, and while it's a little light on the non-parametrics often necessary for behavior (Sokal and Rohlf for those), it's absolutely great for the statistics necessary for ecological and morphological measurements. Very well written, right on that delicate balance between overly dumbed-down and overly jargoned-up.