
Experiments in Ecology
Their Logical Design and Interpretation Using Analysis of Variance
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Product details:
- Publisher Cambridge University Press
- Date of Publication 12 December 1996
- ISBN 9780521556965
- Binding Paperback
- No. of pages524 pages
- Size 229x152x36 mm
- Weight 790 g
- Language English
- Illustrations 81 b/w illus. 94 tables 0
Categories
Short description:
First published in 1996, this book is a logical and consistent approach to experimental design using statistical principles.
MoreLong description:
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, 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 invaluable to practising ecologists as well as advanced students involved in experimental design.
'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
Table of Contents:
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?
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