Simple, clear, and to the point, Probability and Statistics Applications for Environmental Science delineates the fundamentals of statistics, imparting a basic understanding of the theory and mechanics of the calculations. User-friendliness, uncomplicated explanations, and coverage of example applications in the environmental field set this book apart from other textbooks on the same subject. Striking a balance between theory and applied mathematics, the material is divided into three parts. Part I sets the stage with coverage of principles and fundamentals, such as set notation, probability distributions, and the estimation of the mean and variance. Part II discusses traditional statistics applications, centering around the uses of probability distributions, including how they relate to reliability and failure theory. The authors elucidate many of the important distributions, Monte Carlo methods, and fault and event trees. Part III delves into what some have come to define as contemporary statistics. It covers hypothesis testing, Student's t and chi-square tests, regression analysis, analysis of variance (ANOVA), and nonparametric tests. The book's coverage is thorough, its presentation logical and geared to student's needs. It includes problems and solutions within the text and tables, a glossary of terms, and an introduction to design of experiments in the appendices. The authors, known for their meticulously accurate, articulate, and practical writing style, master the difficult task of explaining very complicated subject matter in a way that is easily understood. The book features a clear, concise presentation that makes both teaching and learning easier.

Presenting a nonmathematical approach to this topic, Statistics for Environmental Science and Management introduces frequently used statistical methods and practical applications for the environmental field. This second edition features updated references and examples along with new and expanded material on data quality objectives, the generalized linear model, spatial data analysis, and Monte Carlo risk assessment. Additional topics covered include environmental monitoring, impact assessment, censored data, environmental sampling, the role of statistics in environmental science, assessing site reclamation, and drawing conclusions from data.

In modern society, we are ever more aware of the environmental issues we face, whether these relate to global warming, depletion of rivers and oceans, despoliation of forests, pollution of land, poor air quality, environmental health issues, etc. At the most fundamental level it is necessary to monitor what is happening in the environment – collecting data to describe the changing scene. More importantly, it is crucial to formally describe the environment with sound and validated models, and to analyse and interpret the data we obtain in order to take action. Environmental Statistics provides a broad overview of the statistical methodology used in the study of the environment, written in an accessible style by a leading authority on the subject. It serves as both a textbook for students of environmental statistics, as well as a comprehensive source of reference for anyone working in statistical investigation of environmental issues. Provides broad coverage of the methodology used in the statistical investigation of environmental issues. Covers a wide range of key topics, including sampling, methods for extreme data, outliers and robustness, relationship models and methods, time series, spatial analysis, and environmental standards. Includes many detailed practical and worked examples that illustrate the applications of statistical methods in environmental issues. Authored by a leading authority on environmental statistics.

Simple, clear, and to the point, Probability and Statistics Applications for Environmental Science delineates the fundamentals of statistics, imparting a basic understanding of the theory and mechanics of the calculations. User-friendliness, uncomplicated explanations, and coverage of example applications in the environmental field set this book ap

Statistics is strongly tied to applications in different scientific disciplines, and the most challenging statistical problems arise from problems in the sciences. In fact, the most innovative statistical research flows from the needs of applications in diverse settings. This volume is a testimony to the crucial role that statistics plays in scientific disciplines such as genetics and environmental sciences, among others. The articles in this volume range from human and agricultural genetic DNA research to carcinogens and chemical concentrations in the environment and to space debris and atmospheric chemistry. Also included are some articles on statistical methods which are sufficiently general and flexible to be applied to many practical situations. The papers were refereed by a panel of experts and the editors of the volume. The contributions are based on the talks presented at the Workshop on Statistics and the Sciences, held at the Centro Stefano Franscini in Ascona, Switzerland, during the week of May 23 to 28, 1999. The meeting was jointly organized by the Swiss Federal Institutes of Technology in Lausanne and Zurich, with the financial support of the Minerva Research Foundation. As the presentations at the workshop helped the participants recognize the po tential role that statistics can play in the sciences, we hope that this volume will help the reader to focus on the central role of statistics in the specific areas presented here and to extrapolate the results to further applications.

"Describes the application of statistical methods in different environmental fields, with an emphasis on how to solve real-world problems in complex systems"--Provided by publisher.

A comprehensive treatment of statistical applications for solving real-world environmental problems A host of complex problems face today's earth science community, such as evaluating the supply of remaining non-renewable energy resources, assessing the impact of people on the environment, understanding climate change, and managing the use of water. Proper collection and analysis of data using statistical techniques contributes significantly toward the solution of these problems. Statistics for Earth and Environmental Scientists presents important statistical concepts through data analytic tools and shows readers how to apply them to real-world problems. The authors present several different statistical approaches to the environmental sciences, including Bayesian and nonparametric methodologies. The book begins with an introduction to types of data, evaluation of data, modeling and estimation, random variation, and sampling—all of which are explored through case studies that use real data from earth science applications. Subsequent chapters focus on principles of modeling and the key methods and techniques for analyzing scientific data, including: Interval estimation and Methods for analyzinghypothesis testing of means time series data Spatial statistics Multivariate analysis Discrete distributions Experimental design Most statistical models are introduced by concept and application, given as equations, and then accompanied by heuristic justification rather than a formal proof. Data analysis, model building, and statistical inference are stressed throughout, and readers are encouraged to collect their own data to incorporate into the exercises at the end of each chapter. Most data sets, graphs, and analyses are computed using R, but can be worked with using any statistical computing software. A related website features additional data sets, answers to selected exercises, and R code for the book's examples. Statistics for Earth and Environmental Scientists is an excellent book for courses on quantitative methods in geology, geography, natural resources, and environmental sciences at the upper-undergraduate and graduate levels. It is also a valuable reference for earth scientists, geologists, hydrologists, and environmental statisticians who collect and analyze data in their everyday work.