General experimental techniques and associated theoretical considerations are reviewed, leading to discussion of practical applications in the latter half of the book. Following an introductory chapter, the theoretical basis for more » the various methods of noise analysis is explained, and full chapters are devoted to the fundamentals of statistics for time-domain analysis and Fourier series and related topics for frequency-domain analysis. A major advantage, continuous and undisturbed monitoring, supplies a means of obtaining early warnings of possible reactor malfunctions thus preventing further complications by alerting operators to a problem - and aiding in the diagnosis of that problem - before it demands major repairs. Noise analysis is a growing field that offers advantages such as simplicity, low cost, and natural multivariable interactions. This book concentrates on the different types of noise present in power reactors and how the analysis of this noise can be used as a tool for reactor monitoring and diagnostics. Also, no discussion of methods for assessing risks from environmental pollution could be included. For example, only brief mention could more » be made of time series analysis using Box-Jenkins methods and of kriging techniques for estimating spatial and spatial-time patterns of pollution, although multiple references on these topics are provided. Unfortunately, some important topics could not be included because of their complexity and the need to limit the length of the book. Also, Appendix B lists a computer code that estimates and tests for trends over time at one or more monitoring stations using nonparametric methods (Chapters 16 and 17).

For example, see methods for handling correlated data (Sections 4.5 and 11.12), for detecting hot spots (Chapter 10), and for estimating a confidence interval for the mean of a lognormal distribution (Section 13.2). Some statistical techniques given here are not commonly seen in statistics book. Chapters 4 through 10 discuss field sampling designs and Chapters 11 through 18 deal with a broad range of statistical analysis procedures. Chapters 1, 2, and 3 are introductory chapters. The book is logically divided into three parts.

Most of the statistical techniques are relatively simple, and examples, exercises, and case studies are provided to illustrate procedures. This book fills that need by providing sampling plans, statistical tests, parameter estimation procedure techniques, and references to pertinent publications. The application of statistics to environmental pollution monitoring studies requires a knowledge of statistical analysis methods particularly well suited to pollution data.

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