Description
Book SynopsisEcological 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, first published in 1996, 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
Trade Review'As statistics texts go, this one is a veritable page-turner - sardonic in places, just plain funny in others, and engaging throughout … the clarity of presentation, both rhetorical and logical, is so compelling, that nearly any reader will benefit from examining this volume.' Ted Floyd and Jessica Gurevitch, Trends in Ecology and Evolution
'… comprehensive and often exhaustive, but not exhausting, with many equations leavened by diagrams and graphs.' Simon S. Cross, Biologist
'The material in the book is complemental by the author's rich experience in ecology overthe past 20 years and serves as a reference for those wanting to conduct ecological experiments. there are some valuable insights contained in the book that would aid those involved in spatial and temporatl studies of landscapes and biological responses of different systems.' Journal of Environmental Qual
'Altogether a well-written book that will prove an invaluable resource for ecologists of all calibres.' Helgoländer Meeresuntersuchungen
Table of Contents1. 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?
