Statistics are important tools for validating theory, making predictions and engaging in policy research. They help to provide informed commentary about social and environmental issues, and to make the case for change. Knowledge of statistics is therefore a necessary skill for any student of geography or environmental science. This textbook is aimed at students on a degree course taking a module in statistics for the first time. It focuses on analysing, exploring and making sense of data in areas of core interest to physical and human geographers, and to environmental scientists. It covers the subject in a broadly conventional way from descriptive statistics, through inferential statistics to relational statistics but does so with an emphasis on applied data analysis throughout.

Providing a solid foundation for twenty-first-century scientists and engineers, Data Analysis and Statistics for Geography, Environmental Science, and Engineering guides readers in learning quantitative methodology, including how to implement data analysis methods using open-source software. Given the importance of interdisciplinary work in sustain

Using Statistics to Understand the Environment covers all the basic tests required for environmental practicals and projects and points the way to the more advanced techniques that may be needed in more complex research designs. Following an introduction to project design, the book covers methods to describe data, to examine differences between samples, and to identify relationships and associations between variables. Featuring: worked examples covering a wide range of environmental topics, drawings and icons, chapter summaries, a glossary of statistical terms and a further reading section, this book focuses on the needs of the researcher rather than on the mathematics behind the tests.

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.

Statistics are important tools for validating theory, making predictions and engaging in policy research. They help to provide informed commentary about social and environmental issues, and to make the case for change. Knowledge of statistics is therefore a necessary skill for any student of geography or environmental science. This textbook is aimed at students on a degree course taking a module in statistics for the first time. It focuses on analysing, exploring and making sense of data in areas of core interest to physical and human geographers, and to environmental scientists. It covers the subject in a broadly conventional way from descriptive statistics, through inferential statistics to relational statistics but does so with an emphasis on applied data analysis throughout.