Ecological Models and Data in R

by Benjamin M. Bolker

Ecological Models and Data in R is the first truly practical introduction to modern statistical methods for ecology. In step-by-step detail, the book teaches ecology graduate students and researchers everything they need to know in order to use maximum likelihood, information-theoretic, and Bayesian techniques to analyze their own data using the programming language R. Drawing on extensive experience teaching these techniques to graduate students in ecology, Benjamin Bolker shows how to choose among and construct statistical models for data, estimate their parameters and confidence limits, and interpret the results. The book also covers statistical frameworks, the philosophy of statistical modeling, and critical mathematical functions and probability distributions. It requires no programming background--only basic calculus and statistics.

Genres: Academic, Reference, Ecology

408 pages, Hardcover

First published July 1, 2008

Reviews

[Alissa Mocking · Rating 5 out of 5]

It is not the easiest book to follow sometimes, but it gives a very clear view on ecological models and what you need to understand to build your own models. I could really recommend this to anyone that is advanced in using the basic models and wants to try their hand on something diffrent before diving straight into everything bayesian statics

[Clara Vinyeta · Rating 3 out of 5]

Bolker makes a good introduction to a different way of viewing statistics (Bayesian) and modelling.
However, he expects you to understand a whole complex, abstract concept from one sentence.
My brain gained lots of knowledge, i gained lots of headaches because honestly 90% of the time I was like “yeah nice R code but what are u talking about”. My main issue is that he uses the same examples for every chapter. But those examples are introduced really poorly and by the time I’m in chapter 9, i forgot what the data of the example was. This made it difficult to follow the examples.

[Emily · Rating 3 out of 5]

Wow, I can't believe they have this text on goodreads. I don't know if I'd call it a good read, but it is helping to make the mystery of the R program slightly less mysterious. Only slightly though, because it assumes you know a lot of mathematics (which, let's face it, you probably don't).