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A review by kartrick
The Ecological Detective by Ray Hilborn
4.0
Maybe a 3.5. This is quite the esoteric "book" to review, but my rating obviously stands for my personal enjoyment of the book and the value I gained from it (and completely ignores the effort reading it required).
I first picked up the book in April 2020. It is the first Monograph I have ever read, and I genuinely liked the concept. The physical look and feel of the book as well as the way it is written helps find some middle ground between the conventional textbook and the novel-ish book. The primary reason I picked it up was that I wanted a comprehensive yet beginner-friendly source of statistical information that also illuminated the numerous nuances and guided the reader towards the usually-obscure bridges and links between different concepts. The latter is a persistent problem in any attempt at learning and advancement in the subject of statistics (but in other fields too!). Oh also, the title seemed quite cunning and I just had to read it.
I appreciated how, as this is quite an old book, chapters started from the basics and worked their way up. I think this is vital, because from my experience the knowledge base that students establish by the time they graduate from high school or even an undergraduate degree is often very patchy and the complexities and nuances and even technical details are shrouded if present at all.
Having said that, the authors mostly focus on the manual aspects (as computation, which is so commonplace now, was in its infancy then), and as a result the book is very mathematics- and equation-heavy. I personally loved maths all through school and although I lost touch once I entered university, I was still able to vaguely understand most of the points. I skimmed and even skipped many of the equations though, and ignored those sections that completely went over my head. However, the authors state in the beginning that a mere undergraduate-level of statistical understanding is sufficient to grasp the contents of the book. Having finished reading it, I'm not so sure about that. Perhaps this just goes to show the difference in American education.
Regardless, I found many of the chapters very useful personally, like the ones about likelihood and Bayesian methods. I also loved Chapter 2 which talks about the four fundamental philosophies of (or at least prevalent in) science---well, it's rather that the historical paths are condensed into philosophies. Thomas Chamberlain's article in the Appendix was a really enjoyable read. Even the other chapters contained bits and pieces of important information that helped bring clarity to the fuzz in my head.
Subjects like (but again not limited to) statistics can never be studied in one clean go. There isn't a well-defined path to take, starting from the most basic topics and inching along all the connected ones. Instead, the learning process is often a riot and a mess, with one concept leading you to discover something completely different, and numerous permutations of this until you quite suddenly come upon a link between two separate concepts you'd reached ages ago. And as such, reading this book was great for me. It helped me find a few of these links, and to arrive at a few new checkpoints.
But it also left me wanting a good old one-sitting-fiction next.
I first picked up the book in April 2020. It is the first Monograph I have ever read, and I genuinely liked the concept. The physical look and feel of the book as well as the way it is written helps find some middle ground between the conventional textbook and the novel-ish book. The primary reason I picked it up was that I wanted a comprehensive yet beginner-friendly source of statistical information that also illuminated the numerous nuances and guided the reader towards the usually-obscure bridges and links between different concepts. The latter is a persistent problem in any attempt at learning and advancement in the subject of statistics (but in other fields too!). Oh also, the title seemed quite cunning and I just had to read it.
I appreciated how, as this is quite an old book, chapters started from the basics and worked their way up. I think this is vital, because from my experience the knowledge base that students establish by the time they graduate from high school or even an undergraduate degree is often very patchy and the complexities and nuances and even technical details are shrouded if present at all.
Having said that, the authors mostly focus on the manual aspects (as computation, which is so commonplace now, was in its infancy then), and as a result the book is very mathematics- and equation-heavy. I personally loved maths all through school and although I lost touch once I entered university, I was still able to vaguely understand most of the points. I skimmed and even skipped many of the equations though, and ignored those sections that completely went over my head. However, the authors state in the beginning that a mere undergraduate-level of statistical understanding is sufficient to grasp the contents of the book. Having finished reading it, I'm not so sure about that. Perhaps this just goes to show the difference in American education.
Regardless, I found many of the chapters very useful personally, like the ones about likelihood and Bayesian methods. I also loved Chapter 2 which talks about the four fundamental philosophies of (or at least prevalent in) science---well, it's rather that the historical paths are condensed into philosophies. Thomas Chamberlain's article in the Appendix was a really enjoyable read. Even the other chapters contained bits and pieces of important information that helped bring clarity to the fuzz in my head.
Subjects like (but again not limited to) statistics can never be studied in one clean go. There isn't a well-defined path to take, starting from the most basic topics and inching along all the connected ones. Instead, the learning process is often a riot and a mess, with one concept leading you to discover something completely different, and numerous permutations of this until you quite suddenly come upon a link between two separate concepts you'd reached ages ago. And as such, reading this book was great for me. It helped me find a few of these links, and to arrive at a few new checkpoints.
But it also left me wanting a good old one-sitting-fiction next.