# Statistical Methods for Environmental Pollution Monitoring

John Wiley & Sons, Feb 15, 1987 - Nature - 336 pages
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.

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### Contents

 Sampling Environmental Populations 5 Environmental Sampling Design 17 Simple Random Sampling 26 Stratified Random Sampling 45 TwoStage Sampling 58 Compositing and ThreeStage Sampling 71 Systematic Sampling 89 Double Sampling 106
 Characterizing Lognormal Populations 164 Estimating the Mean and Variance from Censored Data Sets 177 Outlier Detection and Control Charts 186 Detecting and Estimating Trends 204 Trends and Seasonality 225 Comparing Populations 241 Statistical Tables 254 TREND 274

 Locating Hot Spots 119 Quantiles Proportions and Means 132 Skewed Distributions and GoodnessofFit Tests 152