# Statistical Methods for Environmental Pollution Monitoring

John Wiley & Sons, Feb 15, 1987 - Nature - 336 pages
This book discusses a broad range of statistical design andanalysis methods that are particularly well suited to pollutiondata. It explains key statistical techniques in easy-to-comprehendterms and uses practical examples, exercises, and case studies toillustrate procedures. Dr. Gilbert begins by discussing aspace-time framework for sampling pollutants. He then shows how touse statistical sample survey methods to estimate average and totalamounts of pollutants in the environment, and how to determine thenumber of field samples and measurements to collect for thispurpose. Then a broad range of statistical analysis methods aredescribed 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 statisticaltechniques for data that are correlated, reported as less than themeasurement detection limit, or obtained from field-compositedsamples. Nonparametric statistical analysis methods are emphasizedsince parametric procedures are often not appropriate for pollutiondata. This book also provides an illustrated comprehensive computercode for nonparametric trend detection and estimation analyses aswell as nineteen statistical tables to permit easy application ofthe discussed statistical techniques. In addition, manypublications are cited that deal with the design of pollutionstudies and the statistical analysis of pollution data. Thissourcebook will be a useful tool for applied statisticians,ecologists, radioecologists, hydrologists, biologists,environmental engineers, and other professionals who deal with thecollection, 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