Analysis of variance and covariance: how to choose and construct models for the life sciences
Analysis of variance and covariance: how to choose and construct models for the life sciences
Analysis of variance (ANOVA) is a core technique for analysing data in the Life Sciences. This reference book bridges the gap between statistical theory and practical data analysis by presenting a comprehensive set of tables for all standard models of analysis of variance and covariance with up to three treatment factors. The book will serve as a tool to help post-graduates and professionals define their hypotheses, design appropriate experiments, translate them into a statistical model, validate the output from statistics packages and verify results. The systematic layout makes it easy for readers to identify which types of model best fit the themes they are investigating, and to evaluate the strengths and weaknesses of alternative experimental designs. In addition, a concise introduction to the principles of analysis of variance and covariance is provided, alongside worked examples illustrating issues and decisions faced by analysts.
• Pictorial representations of designs and tabulated descriptions help readers differentiate between models and evaluate designs
• Worked examples of the principal models and illustrative examples of applications are developed through this book, bringing the statistics to life
• Chapter on troubleshooting problems, addresses frequently asked questions on data collection, practicalities of analysing data and interpretation of results
Contents:
Preface; Introduction to analysis of variance; Introduction to model structures; 1. One-factor designs; 2. Nested designs; 3. Fully replicated factorial designs; 4. Randomised-block designs; 5. Split-plot designs; 6. Repeated- measures designs; 7. Unreplicated designs; Further topics; Choosing experimental designs; How to request models in a statistics package; Best practice in presentation of the design; Troubleshooting problems during analysis; Glossary; Bibliography; Index of all ANOVA models with up to three factors; Index; Categories of model.
9780521684477
Cambridge University Press
Doncaster, C. Patrick
0eff2f42-fa0a-4e35-b6ac-475ad3482047
Davey, Andrew J.H.
86f3030f-9c68-4708-9fa0-508c5361cf98
August 2007
Doncaster, C. Patrick
0eff2f42-fa0a-4e35-b6ac-475ad3482047
Davey, Andrew J.H.
86f3030f-9c68-4708-9fa0-508c5361cf98
Doncaster, C. Patrick and Davey, Andrew J.H.
(2007)
Analysis of variance and covariance: how to choose and construct models for the life sciences
,
Cambridge, UK.
Cambridge University Press, 302pp.
Abstract
Analysis of variance (ANOVA) is a core technique for analysing data in the Life Sciences. This reference book bridges the gap between statistical theory and practical data analysis by presenting a comprehensive set of tables for all standard models of analysis of variance and covariance with up to three treatment factors. The book will serve as a tool to help post-graduates and professionals define their hypotheses, design appropriate experiments, translate them into a statistical model, validate the output from statistics packages and verify results. The systematic layout makes it easy for readers to identify which types of model best fit the themes they are investigating, and to evaluate the strengths and weaknesses of alternative experimental designs. In addition, a concise introduction to the principles of analysis of variance and covariance is provided, alongside worked examples illustrating issues and decisions faced by analysts.
• Pictorial representations of designs and tabulated descriptions help readers differentiate between models and evaluate designs
• Worked examples of the principal models and illustrative examples of applications are developed through this book, bringing the statistics to life
• Chapter on troubleshooting problems, addresses frequently asked questions on data collection, practicalities of analysing data and interpretation of results
Contents:
Preface; Introduction to analysis of variance; Introduction to model structures; 1. One-factor designs; 2. Nested designs; 3. Fully replicated factorial designs; 4. Randomised-block designs; 5. Split-plot designs; 6. Repeated- measures designs; 7. Unreplicated designs; Further topics; Choosing experimental designs; How to request models in a statistics package; Best practice in presentation of the design; Troubleshooting problems during analysis; Glossary; Bibliography; Index of all ANOVA models with up to three factors; Index; Categories of model.
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Published date: August 2007
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Local EPrints ID: 49504
URI: http://eprints.soton.ac.uk/id/eprint/49504
ISBN: 9780521684477
PURE UUID: 2c123a1c-42da-4348-aac3-ad1626c44bb9
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Date deposited: 13 Nov 2007
Last modified: 28 Apr 2022 01:39
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Author:
Andrew J.H. Davey
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