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Ecological Models and Data in R
Benjamin M. Bolker
€ 70.54
€ 69.84
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Description for Ecological Models and Data in R
Hardback. Offers an introduction to the modern statistical methods for ecology. This book shows how to construct statistical models for data, estimate their parameters and confidence limits, and interpret the results. It covers statistical frameworks, the philosophy of statistical modeling, and critical mathematical functions and probability distributions. Num Pages: 408 pages, 99 line illus. BIC Classification: PBWH; PSAF. Category: (P) Professional & Vocational; (U) Tertiary Education (US: College). Dimension: 262 x 187 x 24. Weight in Grams: 904.
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
Product Details
Publisher
Princeton University Press United States
Number of pages
408
Format
Hardback
Publication date
2008
Condition
New
Number of Pages
408
Place of Publication
New Jersey, United States
ISBN
9780691125220
SKU
V9780691125220
Shipping Time
Usually ships in 4 to 8 working days
Ref
99-1
About Benjamin M. Bolker
Benjamin M. Bolker is a theoretical ecologist in the departments of Mathematics & Statistics and Biology at McMaster University.
Reviews for Ecological Models and Data in R
"Bolker's book is a must-buy for anyone wanting to fit data to models and go beyond hypothesis testing, but it is certainly not an 'introductory' text in the sense of 'simple'. This book is a tour de force for anyone who studied ecology for his or her interest of nature's working. But it is the one single book that can propel the statistical novice to the cutting edge of statistical ecology
albeit with blood, sweat and tears."
Carsten F. Dormann, Basic and Applied Ecology "[A] must for natural scientists and for statisticians who are interested in ecological applications... Numerous enlightening footnotes, meaningful graphics and direct speech are evidence of substantial classroom experience of the author... The book addresses students and researchers who have or have had some basic knowledge in ecology, mathematics and statistics. Delivering many examples and profound details on numerical aspects of maximum likelihood estimation, the book may also give a red line for a course in computational statistics."
Martin Schlather, Biometrical Journal "[T]his book succeeds both in explaining how to analyze many types of ecological data, and in clearly describing the theoretical background behind some common analyses and approaches. I expect to refer to it often."
Lynda D. Prior, Austral Ecology
albeit with blood, sweat and tears."
Carsten F. Dormann, Basic and Applied Ecology "[A] must for natural scientists and for statisticians who are interested in ecological applications... Numerous enlightening footnotes, meaningful graphics and direct speech are evidence of substantial classroom experience of the author... The book addresses students and researchers who have or have had some basic knowledge in ecology, mathematics and statistics. Delivering many examples and profound details on numerical aspects of maximum likelihood estimation, the book may also give a red line for a course in computational statistics."
Martin Schlather, Biometrical Journal "[T]his book succeeds both in explaining how to analyze many types of ecological data, and in clearly describing the theoretical background behind some common analyses and approaches. I expect to refer to it often."
Lynda D. Prior, Austral Ecology