420 pages, figs
The goal of this book is to present skills and knowledge of important statistical concepts through data analytic tools and then apply them to real world problems in the environmental sciences. Since there is no single approach that works best in all research circumstances, the authors introduce models using the frequentist approach, but also discuss Bayesian, nonparametric, and computer intensive methods.
The book begins with an introduction to types of data, evaluation of data, modeling and estimation, random variation, sampling - all of which are explored in the context of case studies, which use real data from earth science applications. Subsequent chapters focus on general principles of modeling (namely formulation, estimation, and evaluation), interval estimation and hypothesis testing of means; regression; methods for analyzing time series data; spatial statistics; multivariate analysis; discrete distributions; and 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. In addition, graphs throughout the book illustrate concepts, identify unusual observations, and assist in model evaluation.
Each chapter concludes with exercises that are designed to elicit understanding of the processes of data analysis, model building, and statistical inference. Solutions to most problems are available on the book's related Web site, along with additional data sets and R-code for most graphs and analyses.
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. (Breitbart.com: Business Wire, 2 March 2011)
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