Environmental and Ecological Statistics with R

Song S. Qian

© 2017 - Chapman and Hall/CRC
Published November 7, 2016
Textbook - 536 Pages - 180 B/W Illustrations
ISBN 9781498728720 - CAT# K25932
Series: Chapman & Hall/CRC Applied Environmental Statistics

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The second edition adds new materials, including:

  • New examples from recent studies on harmful algal blooms and endangered plant species survey, covering linear and nonlinear models, multilevel models, and simulation
  • New sections on self-starter function for nonlinear models, multinomial regression and it's connection to Poisson regression, and nonlinear multilevel models
  • New chapter on using R and RStudio
  • New chapter on using simulation for evaluating a threshold model
  • Exercises to enable use as a course text or for self-study
  • A supplementary GitHub page, including R code and datasets used in the book, and sample chapters.


Emphasizing the inductive nature of statistical thinking, Environmental and Ecological Statistics with R, Second Edition, connects applied statistics to the environmental and ecological fields. Using examples from published works in the ecological and environmental literature, the book explains the approach to solving a statistical problem, covering model specification, parameter estimation, and model evaluation. It includes many examples to illustrate the statistical methods and presents R code for their implementation. The emphasis is on model interpretation and assessment, and using several core examples throughout the book, the author illustrates the iterative nature of statistical inference.

The book starts with a description of commonly used statistical assumptions and exploratory data analysis tools for the verification of these assumptions. It then focuses on the process of building suitable statistical models, including linear and nonlinear models, classification and regression trees, generalized linear models, and multilevel models. It also discusses the use of simulation for model checking, and provides tools for a critical assessment of the developed models. The second edition also includes a complete critique of a threshold model.

Environmental and Ecological Statistics with R, Second Edition focuses on statistical modeling and data analysis for environmental and ecological problems. By guiding readers through the process of scientific problem solving and statistical model development, it eases the transition from scientific hypothesis to statistical model.


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