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ISBN : B005KLQY6I
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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.
- Practical, beginner-friendly introduction to modern statistical techniques for ecology using the programming language R
- Step-by-step instructions for fitting models to messy, real-world data
- Balanced view of different statistical approaches
- Wide coverage of techniques--from simple (distribution fitting) to complex (state-space modeling)
- Techniques for data manipulation and graphical display
- Companion Web site with data and R code for all examples
Download latest books on mediafire and other links compilation Free Ecological Models and Data in R [Kindle Edition]
- File Size: 7243 KB
- Print Length: 408 pages
- Publisher: Princeton University Press; 508 edition (July 1, 2008)
- Sold by: Amazon Digital Services, Inc.
- Language: English
- ASIN: B005KLQY6I
- Text-to-Speech: Enabled
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- Lending: Not Enabled
- Amazon Best Sellers Rank: #486,416 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
- #85
in Kindle Store > Kindle eBooks > Nonfiction > Science > Education > Research - #86
in Kindle Store > Kindle eBooks > Nonfiction > Science > Experiments, Instruments & Measurement > Methodology & Statistics
- #85
in Kindle Store > Kindle eBooks > Nonfiction > Science > Education > Research - #86
in Kindle Store > Kindle eBooks > Nonfiction > Science > Experiments, Instruments & Measurement > Methodology & Statistics
Free Ecological Models and Data in R
This book, in part, was developed from Dr. Bolker's graduate course in Ecological Models and Data at the University of Florida. This was the best course I took as a graduate student, it transformed the set of quantitative tools I was able to bring to bear on ecological questions. There was so much worthwhile material covered in this class that I took it twice (UF only counted the first time:). Since graduate school I still frequently refer to my notes from the class. With the publication of "Ecological Models and Data in R" even those who didn't have the good fortune of being in Bolker's class can learn approaches for integrating ecological theory and data. Bolker's book covers much of the material from his course and thus is an excellent resource for graduate students and faculty alike.
By James R. Vonesh
I'm doing infectious disease modeling for a living, and I got a lot out of this book. I was not too familiar with R and with stochastic models. Reading and working through this book taught me a lot. The book is really meant to be worked through carefully. Ben drops nuggets of wisdom everywhere - but you need to read carefully to catch them. It's not the ideal book if you need a quick reference on how to do "X". But as a textbook and to really learn things, it is great. That said, I would hesitate to use it for a real beginner's class. Some background with statistical concepts and a solid math foundation are necessary. And some programming experience, with either R or another language, helps a lot. If students are too weak in any of these areas, it would be hard to teach the material in a single semester course. But the great thing about this book is that anyone motivated to learn the subject matter can "simply" sit down and work through it on their own and at their own pace. It will take time, but it's totally worth it.
By ah
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