This text focuses on the needs of the researcher and provides a concise introduction to this core area of Environmental Studies. 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. The book explains:
* how to design a research project
* methods to describe data
* how to examine differences between samples
* how to identify relationships and associations between variables.
It features worked examples covering a wide range of environmental topics, clear illustrations, chapter summaries, a glossary of terms and a further reading section.

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.

This book introduces experimental design and data analysis / interpretation as well as field monitoring skills for both plants and animals. Clearly structured throughout and written in a student-friendly manner, the main emphasis of the book concentrates on the techniques required to design a field based ecological survey and shows how to execute an appropriate sampling regime. The book evaluates appropriate methods, including the problems associated with various techniques and their inherent flaws (e.g. low sample sizes, large amount of field or laboratory work, high cost etc). This provides a resource base outlining details from the planning stage, into the field, guiding through sampling and finally through organism identification in the laboratory and computer based data analysis and interpretation.

The text is divided into six distinct chapters. The first chapter covers planning, including health and safety together with information on a variety of statistical techniques for examining and analysing data. Following a chapter dealing with site characterisation and general aspects of species identification, subsequent chapters describe the techniques used to survey and census particular groups of organisms. The final chapter covers interpreting and presenting data and writing up the research. The emphasis here is on appropriate wording of interpretation and structure and content of the report.

Studying invertebrates is a comprehensive guide to designing and carrying out ecological investigations, especially those involving sampling invertebrates. A highly practical guide to fieldwork, statistical testing and interpretation. The book introduces ways of designing and analysing experiments so that complex situations can be described and summarised, comparisons made, and interactions between organisms and their environment examined objectively. This digital reprint replaces ISBN 0-85546-313-9. First published in 2003. Editors' preface The books in this series are designed to encourage readers to undertake their own studies of natural history. Each one describes some relevant techniques, but they have not enough space to cover the substantial body of more generally applicable ideas and approaches that underlies the design and analysis of such field studies. By describing a selection of these general methods, Studying invertebrates aims to support those venturing into ecological fieldwork for the first time. The authors have plenty of experience in helping beginners to plan, carry out and interpret ecological surveys and experiments, and we hope this handbook will serve as a welcome companion and guide, especially for those who lack confidence in their knowledge of statistical and other methods.