"...this book is important for ecologists to read....We do however need the methods of statistical inference
to help sort out the details of ecological problems, and Underwood's important contribution in this book is to
help convince us that the ecological devil is in the details."
--Charles J. Krebs, Revue Des Livres
"There are some valuable insights contained in the book that would aid those involved in spatial and temporal
studies of landscapes and biological responses of different systems. The regression approaches to analyze the relationships
among variables are quite detailed and insightful. It serves as a good reference on analysis of variance...."
--J. Environ. Qual
Cambridge University Press
March, 2000
Summary
Ecological theories and hypotheses are usually complex because of natural variability in space and time, which
often makes the design of experiments difficult. This book describes how to design ecological experiments from
a statistical basis using analysis of variance, so reliable conclusions can be drawn. 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 practicing ecologists as well as advanced
students involved in experimental design.
Table of Contents
Introduction
A framework for investigating biological patterns and processes
Populations, frequency distributions and samples
Statistical tests of null hypotheses
Statistical tests on samples
Simple experiments comparing the means of two populations
Analysis of variance
More analysis of variance
Nested analyses of variance
Factorial experiments
Construction of any analysis from general principles
Some common and some particular experimental designs