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Zusatztext "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. 2004About the first edition:"...a valuable addition to any environmental engineer's library."-Technometrics Informationen zum Autor Linfield C. Brown, Paul Mac Berthouex Klappentext The second edition of this bestseller is 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 so that each one can 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. Zusammenfassung Two critical questions arise when one is confronted with a new problem that involves the collection and analysis of data. How will the use of statistics help solve this problem? Which techniques should be used? This book answers these questions and intends to understand and design systems for environmental protection. Inhaltsverzeichnis Chapter topics include: Environmental Problems and Statistics. A Brief Review of Statistics. Plotting Data. Smoothing Data. Seeing the Shape of a Distribution. External Reference Distributions. Accuracy, Bias, and Precision of Measurements. Precision of Calculated Values. Fundamentals of Process Control Charts. Specialized Control Charts. Limit of Detection. Censored Data. Paired t -Test for Assessing the Average of Differences. Independent t-Test for Assessing the Difference of Two Averages. Multiple Paired Comparison of k Averages. Experimental Design. Sizing the Experiment. Analysis of Variance to Compare k Averages. Components of Variance. Multiple Factor Analysis of Variance. Factorial Experimental Designs. Fractional Factorial Experimental Designs.Correlation. Serial Correlation. The Method of Least Squares. Precision of Parameters in Linear Models. Precision of Parameters in Nonlinear Models. Weighted Least Squares. Empirical Model Building by Linear Regression. The Coefficient of Determination, R2. Data Adjustment for Process Rationalization. How Measurement Errors Propagate into Calculated Values. Using Simulations to Study Statistical Problems. Introduction to Time Series Modeling. Forecasting Time Series. Intervention Analysis. Appendix-Statistical Tables....
