Synopsis
The use of appropriate statistical methods is essential when working with environmental data. Yet, many environmental professionals are not statisticians. A ready reference guide to the most common methods used in environmental applications, Statistics for Environmental Science and Management introduces the statistical methods most frequently used by environmental scientists, managers, and students.
Using a non-mathematical approach, the author describes techniques such as: environmental monitoring, impact assessment, assessing site reclamation, censored data, and Monte Carlo risk assessment, as well as the key topics of time series and spatial data. The book shows the strengths of different types of conclusions available from statistical analyses. It contains internet sources of information that give readers access to the latest information on specific topics.
The author's easy to understand style makes the subject matter accessible to anyone with a rudimentary knowledge of the basics of statistics while emphasizing how the techniques are applied in the environmental field. Clearly and copiously illustrated with line drawings and tables, Statistics for Environmental Science and Management covers all the statistical methods used with environmental applications and is suitable as a text for graduate students in the environmental science area.
Review
A former faculty member who has written books for environmental science and now a statistician for an environmental consulting company, the author knows the needs of environmental environmental scientists. He also knows how to effectively present methodology to his audience...Overall, this book has a huge variety of topics and numerous examples...a great and inexpensive library addition for statisticians and environmental scientists who analyze environmental data.
- Technometrics, May 2002
This book will do much to promote good statistical practice in environmental matters, an area of worldwide concern.
-Short Book Reviews of the ISI, Vol. 21, No. 2, August 2001
It assumes little previous statistical training, and aims to take the reader from basics through the middle ground of modelling and inference to deliver a grounding in advanced techniques appropriate for the specific audience....covers a remarkably broad range of topics for its size...text is commendably clear, describes the objectives as well as the mechanics of particular analyses, and points out some logical difficulties that no amount of statistical wizardry can overcome...provides a clear overview of many statistical techniques, and ample references to further reading...it serves its purpose well.
--D. Elston, Biometrics, June 2001
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