The book is well written, easy to read, and interesting, which is no small feat considering the subject matter. The authors have taken considerable steps to make this textbook user-friendly to their intended audience, environmental engineers. … The authors, both recognized experts in civil and sanitary engineering, provide data and problems in each chapter that use relevant and realistic examples to teach the concepts of each chapter. … [U]seful and well written … [the book] contains exercises based on the types of real-world problems that environmental engineers face on a daily basis.
- Environmental Practice, Vol. 6, No. 4, Dec. 2004
The second edition of this bestseller serves as an ideal textbook for students and a valuable reference for environmental scientists and engineers. Written in an easy-to-understand style, Statistics for Environmental Engineers, Second Edition consists of 54 short, "stand-alone" chapters. All chapters address a particular environmental problem or statistical technique and are written in a manner that permits each chapter to be studied independently and in any order. Chapters are organized around specific case studies, beginning with brief discussions of the appropriate methodologies, followed by analysis of the case study examples, and ending with comments on the strengths and weaknesses of the approaches.
The book is not about the environmental systems, except incidentally. It is about how to extract information from data and how informative data are generated in the first place. A selection of practical statistical methods is applied to the kinds of problems that we encountered in our work. We have not tried to discuss every statistical method that is useful for studying environmental data. To do so would mean including virtually all statistical methods, an obvious impossibility. Likewise, it is impossible to mention every environmental problem that can or should be investigated by statistical methods. Each reader, therefore, will find gaps in our coverage; when this happens, we hope that other authors have filled the gap. Indeed, some topics have been omitted precisely because we know they are discussed in other well-known books.
It is important to encourage engineers to see statistics as a professional tool used in familiar examples that are similar to those faced in one’s own work. For most of the examples in this book, the environmental engineer will have a good idea how the test specimens were collected and how the measurements were made. The data thus have a special relevance and reality that should make it easier to understand special features of the data and the potential problems associated with the data analysis.
The book is organized into short chapters. The goal was for each chapter to stand alone so one need not study the book from front to back, or in any other particular order. Total independence of one chapter from another is not always possible, but the reader is encouraged to “dip in” where the subject of the case study or the statistical method stimulates interest. For example, an engineer whose current interest is fitting a kinetic model to some data can get some useful ideas from Chapter 25 without first reading the preceding 24 chapters. To most readers, Chapter 25 is not conceptually more difficult than Chapter 12. Chapter 40 can be understood without knowing anything about t-tests, confidence intervals, regression, or analysis of variance.