Gibbons / Bhaumik / Aryal Statistical Methods for Groundwater Monitoring

2. Auflage 2009
ISBN: 978-0-470-54992-6
Verlag: John Wiley & Sons
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 416 Seiten, E-Book

Reihe: Statistics in Practice

A new edition of the most comprehensive overview of statisticalmethods for environmental monitoring applications
Thoroughly updated to provide current research findings,Statistical Methods for Groundwater Monitoring, SecondEdition continues to provide a comprehensive overview andaccessible treatment of the statistical methods that are useful inthe analysis of environmental data. This new edition expands focuson statistical comparison to regulatory standards that are a vitalpart of assessment, compliance, and corrective action monitoring inthe environmental sciences.
The book explores quantitative concepts useful for surface watermonitoring as well as soil and air monitoring applications whilealso maintaining a focus on the analysis of groundwater monitoringdata in order to detect environmental impacts from a variety ofsources, such as industrial activity and waste disposal. Theauthors introduce the statistical properties of alternativeapproaches, such as false positive and false negative rates, thatare associated with each test and the factors related to theseerror rates. The Second Edition also features:
* An introduction to Intra-laboratory Calibration Curves andrandom-effects regression models for non-constant measurementvariability
* Coverage of statistical prediction limits for agamma-distributed random variable, with a focus on estimation andtesting of parameters in environmental monitoring applications
* A unified treatment of censored data with the computation ofstatistical prediction, tolerance, and control limits
* Expanded coverage of statistical issues related to laboratorypractice, such as detection and quantitation limits
* An updated chapter on regulatory issues that outlines commonmistakes to avoid in groundwater monitoring applications as well asan introduction to the newest regulations for both hazardous andmunicipal solid waste facilities
Each chapter provides a general overview of a problem, followedby statistical derivation of the solution and a relevant examplecomplete with computational details that allow readers to performroutine application of the statistical results. Relevant issues arehighlighted throughout, and recommendations are also provided forspecific problems based on characteristics such as number ofmonitoring wells, number of constituents, distributional form ofmeasurements, and detection frequency.
Statistical Methods for Groundwater Monitoring, SecondEdition is an excellent supplement to courses on environmentalstatistics at the upper-undergraduate and graduate levels. It isalso a valuable resource for researchers and practitioners in thefields of biostatistics, engineering, and the environmentalsciences who work with statistical methods in their everydaywork.

Autoren/Hrsg.

Gibbons, Robert D.

Bhaumik, Dulal

Bhaumik, Dulal K.

Aryal, Subhash

Über Autor(innen)

Robert D. Gibbons, PhD, is Director of the Center for HealthStatistics and Professor of Biostatistics and Psychiatry at theUniversity of Illinois at Chicago. A Fellow of the AmericanStatistical Association and member of the Institute of Medicine ofthe National Academy of Sciences, Dr. Gibbons has written more than200 journal articles in the areas of statistics and psychometrics.He is the coauthor of Longitudinal Data Analysis andStatistical Methods for Detection and Quantification ofEnvironmental Contamination, both published by Wiley.
DULAL K. BHAUMIK, PhD, is Professor of Biostatistics,Psychiatry, and Bioengineering at the University of Illinois atChicago. A Fellow of the American Statistical Association, Dr.Bhaumik has published more than fifty journal articles in his areasof research interest, which include environmental statistics,statistical problems in psychiatry, biostatistics, design ofexperiments, and statistical inference.
SUBHASH ARYAL, PhD, is Assistant Professor ofBiostatistics at the University of North Texas Health ScienceCenter at Fort Worth. He has coauthored numerous published articleson statistics in the environmental sciences.