Analyzing Environmental Data

Walter W. Piegorsch, A. John Bailer

• Publisher: Wiley
• Year: 2005
• Print ISBN: 9780470848364
• eBook ISBN: 9780470012222
• Edition: 1
• Topic: Mathematics
• Subtopic: Probability & Statistics
• Index: Mathematics

Environmental statistics is a rapidly growing field, supported by advances in digital computing power, automated data collection systems, and interactive, linkable Internet software. Concerns over public and ecological health and the continuing need to support environmental policy-making and regulation have driven a concurrent explosion in environmental data analysis. This textbook is designed to address the need for trained professionals in this area. The book is based on a course which the authors have taught for many years, and prepares students for careers in environmental analysis centered on statistics and allied quantitative methods of data evaluation. The text extends beyond the introductory level, allowing students and environmental science practitioners to develop the expertise to design and perform sophisticated environmental data analyses. In particular, it:

• Provides a coherent introduction to intermediate and advanced methods for modeling and analyzing environmental data.
• Takes a data-oriented approach to describing the various methods.
• Illustrates the methods with real-world examples
• Features extensive exercises, enabling use as a course text.
• Includes examples of SAS computer code for implementation of the statistical methods.
• Connects to a Web site featuring solutions to exercises, extra computer code, and additional material.
• Serves as an overview of methods for analyzing environmental data, enabling use as a reference text for environmental science professionals.

Graduate students of statistics studying environmental data analysis will find this invaluable as will practicing data analysts and environmental scientists including specialists in atmospheric science, biology and biomedicine, chemistry, ecology, environmental health, geography, and geology.

Table of contents

• Analyzing Environmental Data