Their Logical Design and Interpretation Using Analysis of Variance
Buch, Englisch, 522 Seiten, Format (B × H): 157 mm x 235 mm, Gewicht: 993 g
ISBN: 978-0-521-55329-2
Verlag: Cambridge University Press
Ecological theories and hypotheses are usually complex because of natural variability in space and time, which often makes the design of experiments difficult. The statistical tests we use require data to be collected carefully and with proper regard to the needs of these tests. This book describes how to design ecological experiments from a statistical basis using analysis of variance, so that we can draw reliable conclusions. The logical procedures that lead to a need for experiments are described, followed by an introduction to simple statistical tests. This leads to a detailed account of analysis of variance, looking at procedures, assumptions and problems. One-factor analysis is extended to nested (hierarchical) designs and factorial analysis. Finally, some regression methods for examining relationships between variables are covered. Examples of ecological experiments are used throughout to illustrate the procedures and examine problems. This book will be invaluable to practising ecologists as well as advanced students involved in experimental design.
Autoren/Hrsg.
Fachgebiete
- Naturwissenschaften Biowissenschaften Biowissenschaften Terrestrische Ökologie
- Geowissenschaften Geologie Paläoökologie
- Geowissenschaften Geologie Umweltgeologie, Geoökologie
- Naturwissenschaften Biowissenschaften Biowissenschaften Meeres- und Süßwasserökologie
- Naturwissenschaften Physik Angewandte Physik Soziophysik, Wirtschaftsphysik
- Geowissenschaften Umweltwissenschaften Angewandte Ökologie
- Naturwissenschaften Biowissenschaften Biowissenschaften Ökologie
- Geowissenschaften Umweltwissenschaften Umweltüberwachung, Umweltanalytik, Umweltinformatik
- Naturwissenschaften Biowissenschaften Biowissenschaften Naturschutzbiologie, Biodiversität
Weitere Infos & Material
1. Introduction; 2. A framework for investigating biological patterns and processes; 3. Populations, frequency distributions and samples; 4. Statistical tests of null hypotheses; 5. Statistical tests on samples; 6. Simple experiments comparing the means of two populations; 7. Analysis of variance; 8. More analysis of variance; 9. Nested analyses of variance; 10. Factorial experiments; 11. Construction of any analysis from general principles; 12. Some common and some particular experimental designs; 13. Analysis involving relationships among variables; 14. Conclusions: where to from here?
