| Titre : |
Analysing ecological data |
| Type de document : |
livre |
| Auteurs : |
Zuur, Alain F., Auteur ; Ieno, Elena N., Auteur ; Graham M. Smith, Auteur |
| Editeur : |
New York : Springer |
| Année de publication : |
2007 |
| Collection : |
Statistics for biology and health |
| Importance : |
672 p. |
| ISBN/ISSN/EAN : |
978-0-387-45967-7 |
| Note générale : |
DOI:10.1007/978-0-387-45972-1 |
| Langues : |
Anglais (eng) |
| Mots-clés : |
Animal ecology Ecology Plant ecology Statistical methods |
| Résumé : |
La 4ème de couv. indique : This book provides a practical introduction to analysing ecological data using real data sets collected as part of postgraduate ecological studies or research projects.
The first part of the book gives a largely non-mathematical introduction to data exploration, univariate methods (including GAM and mixed modelling techniques), multivariate analysis, time series analysis (e.g. common trends) and spatial statistics. The second part provides 17 case studies, mainly written together with biologists who attended courses given by the first authors. The case studies include topics ranging from terrestrial ecology to marine biology. The case studies can be used as a template for your own data analysis; just try to find a case study that matches your own ecological questions and data structure, and use this as starting point for you own analysis. Data from all case studies are available from www.highstat.com. Guidance on software is provided in Chapter 2. |
| En ligne : |
https://doi.org/10.1007/978-0-387-45972-1 |
Analysing ecological data [livre] / Zuur, Alain F., Auteur ; Ieno, Elena N., Auteur ; Graham M. Smith, Auteur . - New York : Springer, 2007 . - 672 p.. - ( Statistics for biology and health) . ISBN : 978-0-387-45967-7 DOI:10.1007/978-0-387-45972-1 Langues : Anglais ( eng)
| Mots-clés : |
Animal ecology Ecology Plant ecology Statistical methods |
| Résumé : |
La 4ème de couv. indique : This book provides a practical introduction to analysing ecological data using real data sets collected as part of postgraduate ecological studies or research projects.
The first part of the book gives a largely non-mathematical introduction to data exploration, univariate methods (including GAM and mixed modelling techniques), multivariate analysis, time series analysis (e.g. common trends) and spatial statistics. The second part provides 17 case studies, mainly written together with biologists who attended courses given by the first authors. The case studies include topics ranging from terrestrial ecology to marine biology. The case studies can be used as a template for your own data analysis; just try to find a case study that matches your own ecological questions and data structure, and use this as starting point for you own analysis. Data from all case studies are available from www.highstat.com. Guidance on software is provided in Chapter 2. |
| En ligne : |
https://doi.org/10.1007/978-0-387-45972-1 |
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