Berkshire Encyclopedia of Sustainability - Vol. 6: Measurements, Indicators, and Research Methods for Sustainability by
Measurements, Indicators, and Research Methods for Sustainability presents a thorough and accessible overview of the ways in which sustainability is charted worldwide. Some articles introduce basic concepts, such as quantitative versus qualitative data or the weak versus strong sustainability debate; others examine how indicators in specific areas (climate change, soil conservation, agriculture and mining) have been applied (or not) to different regions. Research analysts explain the modes and media through which these measurements are broadcast, stressing the importance of developing methods that can be understood by both experts and ordinary citizens. They also examine the process of monitoring, itself a controversial topic affecting national or international policy, law, rules, and regulations.
Excel 2016 for Environmental Sciences Statistics by
This book shows the capabilities of Microsoft Excel in teaching environmental science statistics effectively. Similar to the previously published Excel 2013 for Environmental Sciences Statistics, this book is a step-by-step exercise-driven guide for students and practitioners who need to master Excel to solve practical environmental science problems. If understanding statistics isn't the reader's strongest suit, the reader is not mathematically inclined, or if the reader is new to computers or to Excel, this is the book to start off with. Excel, a widely available computer program for students and managers, is also an effective teaching and learning tool for quantitative analyses in environmental science courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. However, Excel 2016 for Environmental Sciences Statistics: A Guide to Solving Practical Problems capitalizes on these improvements by teaching students and managers how to apply Excel to statistical techniques necessary in their courses and work. Each chapter explains statistical formulas and directs the reader to use Excel commands to solve specific, easy-to-understand environmental science problems. Practice problems are provided at the end of each chapter with their solutions in an appendix. Separately, there is a full Practice Test (with answers in an Appendix) that allows readers to test what they have learned.
An Introduction to Scientific Research Methods in Geography and Environmental Studies by
This revised, updated, and extended Second Edition of An Introduction to Scientific Research Methods in Geography and Environmental Studies provides a broad and integrative introduction to the conduct and interpretation of scientific research in geography. It explains both, the conceptual and the technical aspects of research, as well as all phases of the research process. The text continues to be inclusive: combining approaches in physical geography, human geography, and techniques (such as GIS, cartography, and remote sensing). As in the previous edition, the authors use a framework - of a natural and social scientific approach - common to all subjects in geography.In this edition new material is included on "Computational Modeling", as well as more information about GPS and map projections, as well as an expanded chapter on Scientific Communication to present more guidance on writing a literature review. Each chapter has a short case study of actual research projects in order to demonstrate the breadth of approaches taken in scientific research in geography. Fully updated, including references and further readings, the text includes links to relevant web sites.
Research Methods for Environmental Studies by
The methodological needs of environmental studies are unique in the breadth of research questions that can be posed, calling for a textbook that covers a broad swath of approaches to conducting research with potentially many different kinds of evidence.　　 Written specifically for social science-based research into the environment, this book covers the best-practice research methods most commonly used to study the environment and its connections to societal and economic activities and objectives. Over five key parts, Kanazawa introduces quantitative and qualitative approaches, mixed methods, and the special requirements of interdisciplinary research, emphasizing that methodological practice should be tailored to the specific needs of the project. Within these parts, detailed coverage is provided on key topics including the identification of a research project; spatial analysis; ethnography approaches; interview technique; and ethical issues in environmental research.　 Drawing on a variety of extended examples to encourage problem-based learning and fully addressing the challenges associated with interdisciplinary investigation, this book will be an essential resource for students embarking on courses exploring research methods in environmental studies.
Statistical Data Analysis Explained by
Few books on statistical data analysis in the natural sciences are written at a level that a non-statistician will easily understand. This is a book written in colloquial language, avoiding mathematical formulae as much as possible, trying to explain statistical methods using examples and graphics instead. To use the book efficiently, readers should have some computer experience. The book starts with the simplest of statistical concepts and carries readers forward to a deeper and more extensive understanding of the use of statistics in environmental sciences. The book concerns the application of statistical and other computer methods to the management, analysis and display of spatial data. These data are characterised by including locations (geographic coordinates), which leads to the necessity of using maps to display the data and the results of the statistical methods. Although the book uses examples from applied geochemistry, and a large geochemical survey in particular, the principles and ideas equally well apply to other natural sciences, e.g., environmental sciences, pedology, hydrology, geography, forestry, ecology, and health sciences/epidemiology. The book is unique because it supplies direct access to software solutions (based on R, the Open Source version of the S-language for statistics) for applied environmental statistics. For all graphics and tables presented in the book, the R-scripts are provided in the form of executable R-scripts. In addition, a graphical user interface for R, called DAS+R, was developed for convenient, fast and interactive data analysis. Statistical Data Analysis Explained: Applied Environmental Statistics with R provides, on an accompanying website, the software to undertake all the procedures discussed, and the data employed for their description in the book.
Using Statistics to Understand the Environment by
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.
Practical Applications of Environmental Statistics and Data Analysis by
'Practical Applications of Environmental Statistics and Data Analysis' is an introduction to modern environmental statistics and related applications currently used in solving real-world problems in complex systems.
Analyzing Environmental Data by
Environmental statistics is a rapidly growing field, supported by advances in digital computing power, automated data collection systems, and interactive, linkable Internet software. Concerns over public and ecological health and the continuing need to support environmental policy-making and regulation have driven a concurrent explosion in environmental data analysis. This textbook is designed to address the need for trained professionals in this area. The book is based on a course which the authors have taught for many years, and prepares students for careers in environmental analysis centered on statistics and allied quantitative methods of data evaluation. The text extends beyond the introductory level, allowing students and environmental science practitioners to develop the expertise to design and perform sophisticated environmental data analyses. In particular, it: Provides a coherent introduction to intermediate and advanced methods for modeling and analyzing environmental data. Takes a data-oriented approach to describing the various methods. Illustrates the methods with real-world examples Features extensive exercises, enabling use as a course text. Includes examples of SAS computer code for implementation of the statistical methods. Connects to a Web site featuring solutions to exercises, extra computer code, and additional material. Serves as an overview of methods for analyzing environmental data, enabling use as a reference text for environmental science professionals. Graduate students of statistics studying environmental data analysis will find this invaluable as will practicing data analysts and environmental scientists including specialists in atmospheric science, biology and biomedicine, chemistry, ecology, environmental health, geography, and geology.