Customer Rating: 
Summary: A ripping yarn
Comment: Book arrive promptly and in excellent condition. It covers statisitcs for field ecologists in a clear and conscise manner. Worth the money.
Customer Rating:
Summary: Great book!
Comment: Great book, clean language. A good start for anyone who want to learn statistics and somenting else.
Customer Rating:
Summary: Primer is truly helpful
Comment: 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.
Customer Rating:
Summary: Statistics for people with muddy boots
Comment: 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.
Summary: A ripping yarn
Comment: Book arrive promptly and in excellent condition. It covers statisitcs for field ecologists in a clear and conscise manner. Worth the money.
Customer Rating:
Summary: Great book!
Comment: Great book, clean language. A good start for anyone who want to learn statistics and somenting else.
Customer Rating:
Summary: Primer is truly helpful
Comment: 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.
Customer Rating:
Summary: Statistics for people with muddy boots
Comment: 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.