Experiments in ecology : their logical design and interpretation using analysis of variance / A.J. Underwood.

Format:

Book

Author/Creator:

Underwood, A. J., author.

Language:

English

Subjects (All):

Ecology--Experiments.

Ecology.

Physical Description:

1 online resource (xviii, 504 pages) : digital, PDF file(s).

Place of Publication:

Cambridge : Cambridge University Press, 1997.

Language Note:

English

Summary:

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.

Contents:

Cover; Half-title; Title; Copyright; Contents; Acknowledgements; 1 Introduction; 2 A framework for investigating biological patterns and processes; 2.1 Introduction; 2.2 Observations; 2.3 Models, theories, explanations; 2.3.1 Models of physiological stress; 2.3.2 Models based on competition; 2.3.3 Grazing models; 2.3.4 Models to do with hazards; 2.3.5 Models of failure of recruitment; 2.4 Numerous competing models; 2.5 Hypotheses, predictions; 2.6 Null hypotheses; 2.7 Experiments and their interpretation; 2.8 What to do next?; 2.9 Measurements, gathering data and a logical structure

2.10 A consideration: why are you measuring things?2.11 Conclusion: a plea for more thought; 3 Populations, frequency distributions and samples; 3.1 Introduction; 3.2 Variability in measurements; 3.3 Observations and measurements as frequency distributions; 3.4 Defining the population to be observed; 3.5 The need for samples; 3.6 The location parameter; 3.7 Sample estimate of the location parameter; 3.8 The dispersion parameter; 3.9 Sample estimate of the dispersion parameter; 3.10 Degrees of freedom; 3.11 Representative sampling and accuracy of samples; 3.12 Other useful parameters

3.12.1 Skewness3.12.2 Kurtosis; 4 Statistical tests of null hypotheses; 4.1 Why a statistical test?; 4.2 An example using coins; 4.3 The components of a statistical test; 4.3.1 Null hypothesis; 4.3.2 Test statistic; 4.3.3 Region of rejection and critical value; 4.4 Type I error or rejection of a true null hypothesis; 4.5 Statistical test of a theoretical biological example; 4.5.1 Transformation of a normal distribution to the standard normal distribution; 4.6 One- and two-tailed null hypotheses; 5 Statistical tests on samples; 5.1 Repeated sampling

5.2 The standard error from the normal distribution of sample means5.3 Confidence intervals for a sampled mean; 5.4 Precision of a sample estimate of the mean; 5.5 A contrived example of use of the confidence interval of sampled means; 5.6 Student's t-distribution; 5.7 Increasing precision of sampling; 5.7.1 The chosen probability used to construct the confidence interval; 5.7.2 The sample size (n); 5.7.3 The variance of the population (σ2); 5.8 Description of sampling; 5.9 Student's t-test for a mensurative hypothesis; 5.10 Goodness-of-fit, mensurative experiments and logic

5.11 Type I and Type II errors in relation to a null hypothesis5.12 Determining the power of a simple statistical test; 5.12.1 Probability of Type I error; 5.12.2 Size of experiment (n); 5.12.3 Variance of the population; 5.12.4 'Effect size'; 5.13 Power and alternative hypotheses; 6 Simple experiments comparing the means of two populations; 6.1 Paired comparisons; 6.2 Confounding and lack of controls; 6.3 Unpaired experiments; 6.4 Standard error of the difference between two means; 6.4.1 Independence of samples; 6.4.2 Homogeneity of variances; 6.5 Allocation of sample units to treatments

6.6 Interpretation of a simple ecological experiment

Notes:

Title from publisher's bibliographic system (viewed on 05 Oct 2015).

Includes bibliographical references (pages 486-495) and indexes.

ISBN:

1-107-08473-3

1-316-08735-2

1-107-08891-7

1-107-10075-5

1-107-09510-7

0-511-80640-X