Statistical Methods for Groundwater Monitoring / Edition 2

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Overview

This book explains the statistical methods used to analyze the huge volume of data that groundwater monitoring wells produce in a comprehensive manner accessible to engineers and scientists who may not have a strong background in statistics. In addition, the book provides statistical methods to make the most accurate use of the data and shows how to set up an effective monitoring system.
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Editorial Reviews

Booknews
Many environmental policies are based on the monitoring of groundwater to determine if and how much hazardous waste is being released from a storage facility, even though the interpretation of measurements is based on inappropriate statistical models. Each of the chapters here begins with an overview of one aspect of the problem, then presents increasingly complex statistical solutions. The clustering of chapters indicates the interrelation of the various problems, such as nonparametric prediction intervals, practical quantitation limits, censored data, and detecting outliers. Annotation c. Book News, Inc., Portland, OR (booknews.com)
From the Publisher
"This book is an excellent supplementary text for courses on environmental statistics or reference for researchers and practitioners." (Book News, December 2009)
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Product Details

  • ISBN-13: 9780470164969
  • Publisher: Wiley, John & Sons, Incorporated
  • Publication date: 10/12/2009
  • Series: Statistics in Practice Series , #59
  • Edition description: New Edition
  • Edition number: 2
  • Pages: 374
  • Sales rank: 1,116,765
  • Product dimensions: 6.20 (w) x 9.10 (h) x 0.90 (d)

Meet the Author

Robert D. Gibbons, PhD, is Director of the Center for Health Statistics and Professor of Biostatistics and Psychiatry at the University of Illinois at Chicago. A Fellow of the American Statistical Association and member of the Institute of Medicine of the National Academy of Sciences, Dr. Gibbons has written more than 200 journal articles in the areas of statistics and psychometrics. He is the coauthor of Longitudinal Data Analysis and Statistical Methods for Detection and Quantification of Environmental Contamination, both published by Wiley.

DULAL K. BHAUMIK, PhD, is Professor of Biostatistics, Psychiatry, and Bioengineering at the University of Illinois at Chicago. A Fellow of the American Statistical Association, Dr. Bhaumik has published more than fifty journal articles in his areas of research interest, which include environmental statistics, statistical problems in psychiatry, biostatistics, design of experiments, and statistical inference.

SUBHASH ARYAL, PhD, is Assistant Professor of Biostatistics at the University of North Texas Health Science Center at Fort Worth. He has coauthored numerous published articles on statistics in the environmental sciences.

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Table of Contents

Introduction 1
1 Normal Prediction Intervals 8
2 Nonparametric Prediction Intervals 33
3 Prediction Intervals for Other Distributions 77
4 Tolerance Intervals 84
5 Method Detection Limits 95
6 Practical Quantitation Limits 122
7 Contaminant Source Analysis 132
8 Intrawell Comparisons 160
9 Trend Analysis 175
10 Censored Data 186
11 Tests for Departure from Normality 216
12 Variance Component Models 236
13 Detecting Outliers 246
14 Applications to Regulatory Issues 258
Summary 270
References 272
Index 281
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