Analyzing Ecological Data

Alain Zuur

ISBN 10: 1441923578 / ISBN 13: 9781441923578

Verlag: Springer New York, Springer US Feb 2011, 2011

Beschreibung

Neuware -'Which test should I apply ' During the many years of working with ecologists, biologists and other environmental scientists, this is probably the question that the authors of this book hear the most often. The answer is always the same and along the lines of 'What are your underlying questions ', 'What do you want to show '. The answers to these questions provide the starting point for a detailed discussion on the ecological background and purpose of the study. This then gives the basis for deciding on the most appropriate analytical approach. Therefore, a better start ing point for an ecologist is to avoid the phrase 'test' and think in terms of 'analy sis'. A test refers to something simple and unified that gives a clear answer in the form of a p-value: something rarely appropriate for ecological data. In practice, one has to apply a data exploration, check assumptions, validate the models, per haps apply a series of methods, and most importantly, interpret the results in terms of the underlying ecology and the ecological questions being investigated. Ecology is a quantitative science trying to answer difficult questions about the complex world we live in. Most ecologists are aware of these complexities, but few are fully equipped with the statistical sophistication and understanding to deal with them.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 700 pp. Englisch.

Bestandsnummer des Verkäufers 9781441923578

Bibliografische Details

• Titel: Analyzing Ecological Data
• Verlag: Springer New York, Springer US Feb 2011
• Erscheinungsjahr: 2011
• Sprache: Englisch
• ISBN-10: 1441923578
• ISBN-13: 9781441923578
• Einband: Taschenbuch
• Zustand: Neu

Über diesen Titel

Inhaltsangabe

This book provides a practical introduction to analyzing ecological data using real data sets collected as part of postgraduate ecological studies or research projects. The first part gives a largely non-mathematical introduction to data exploration, univariate methods (including GAM and mixed modeling techniques), multivariate analysis, time series analysis, and spatial statistics. The second part provides 17 case studies, mainly written together with biologists who attended courses given by the authors. The case studies include topics ranging from terrestrial ecology to marine biology and can be used as a template for a reader’s own data analysis. The case studies also show how to deal with certain levels of difficulty during the key process of selecting the correct or appropriate statistical technique. Data from all case studies are available from www.highstat.com. Guidance on software is provided in the book.

Über die Autorin bzw. den Autor

Grad students, researchers