Statistical Methods For Environmental Pollution Monitoring
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Statistical Methods for Environmental Pollution Monitoring
Author: Richard O. Gilbert
language: en
Publisher: John Wiley & Sons
Release Date: 1987-02-15
This book discusses a broad range of statistical design and analysis methods that are particularly well suited to pollution data. It explains key statistical techniques in easy-to-comprehend terms and uses practical examples, exercises, and case studies to illustrate procedures. Dr. Gilbert begins by discussing a space-time framework for sampling pollutants. He then shows how to use statistical sample survey methods to estimate average and total amounts of pollutants in the environment, and how to determine the number of field samples and measurements to collect for this purpose. Then a broad range of statistical analysis methods are described and illustrated. These include: * determining the number of samples needed to find hot spots * analyzing pollution data that are lognormally distributed * testing for trends over time or space * estimating the magnitude of trends * comparing pollution data from two or more populations New areas discussed in this sourcebook include statistical techniques for data that are correlated, reported as less than the measurement detection limit, or obtained from field-composited samples. Nonparametric statistical analysis methods are emphasized since parametric procedures are often not appropriate for pollution data. This book also provides an illustrated comprehensive computer code for nonparametric trend detection and estimation analyses as well as nineteen statistical tables to permit easy application of the discussed statistical techniques. In addition, many publications are cited that deal with the design of pollution studies and the statistical analysis of pollution data. This sourcebook will be a useful tool for applied statisticians, ecologists, radioecologists, hydrologists, biologists, environmental engineers, and other professionals who deal with the collection, analysis, and interpretation of pollution in air, water, and soil.
Statistical Methods for Detection and Quantification of Environmental Contamination
Author: Robert D. Gibbons
language: en
Publisher: John Wiley & Sons
Release Date: 2001-07-13
Amstat News asked three review editors to rate their top five favorite books in the September 2003 issue. Statistical Methods for Detection and Quantification of Environmental Contamination was among those chosen. This groundbreaking volume describes the statistical theory that underlies the detection and quantification of environmental pollution both in the laboratory and in the field. It presents the foundation of relating measured concentrations to true concentrations and the development of intervals of uncertainty for true concentrations, and it presents a comprehensive review of the problem of estimating thresholds at which detection and quantification decisions can be made reliably. The authors demonstrate the use of analytical measurements in making environmental impact decisions and in comparing environmental data to regulatory standards and naturally occurring background concentrations. Taking the next step in a major evolution in the way environmental impact decisions are made, Statistical Methods for Detection and Quantification of Environmental Contamination: Presents statistical methods that allow the earliest possible detection and quantification of contaminants Describes procedures applicable to all environmental constituents Covers numerous state-of-the-art approaches Includes case studies demonstrating practical applications of these approaches An indispensable handbook for scientists and engineers involved in environmental monitoring programs, this book is also an important resource for public health officials, waste facility managers, regulators, statisticians, and analytical chemists.
Statistical Methods for Environmental and Agricultural Sciences
The first edition of this book, popular around the world, is surpassed only by this new Second Edition. Improvements such as new and revised exercises, a broad range of practical and relevant case studies, and expanded theoretical concepts make this even better for users of statistics. The book emphasizes the practical application of statistics and provides examples in various fields of environmental and agriculture sciences. Because it uses simple, non-mathematical language to present statistical techniques, the reader requires only a familiarity with elementary algebra and mathematical notations to understand and apply the concepts described. This logically organized book covers the following topics: Part 1 introduces statistical concepts as they apply to different fields of environmental and agriculture sciences and provides descriptive measures of central tendency and variability; Part 2 covers probability and sampling concepts used in inferential statistics; Part 3 presents parametric methods in hypothesis testing, which include research designs; Part 4 discusses a number of nonparametric techniques; Part 5 explains tests of association and prediction; and lastly, analysis of change over time is detailed in Part 6. The appendices contain statistical tables for reference purposes.