Authors:
- Presents a thorough overview of the design and analysis of experiments
- Discusses and applies effect size measures and their estimation
- Provides datasets and R code, allowing the reader to reproduce the examples
- Introduces Hasse diagrams for visualizing and constructing designs
- Includes a discussion on good statistical practice
- Illustrated with real-life examples
Part of the book series: Statistics for Biology and Health (SBH)
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Table of contents (10 chapters)
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Front Matter
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Back Matter
About this book
This richly illustrated book provides an overview of the design and analysis of experiments with a focus on non-clinical experiments in the life sciences, including animal research. It covers the most common aspects of experimental design such as handling multiple treatment factors and improving precision. In addition, it addresses experiments with large numbers of treatment factors and response surface methods for optimizing experimental conditions or biotechnological yields.
The book emphasizes the estimation of effect sizes and the principled use of statistical arguments in the broader scientific context. It gradually transitions from classical analysis of variance to modern linear mixed models, and provides detailed information on power analysis and sample size determination, including ‘portable power’ formulas for making quick approximate calculations. In turn, detailed discussions of several real-life examples illustrate the complexities and aberrations that can arise in practice.
Chiefly intended for students, teachers and researchers in the fields of experimental biology and biomedicine, the book is largely self-contained and starts with the necessary background on basic statistical concepts. The underlying ideas and necessary mathematics are gradually introduced in increasingly complex variants of a single example. Hasse diagrams serve as a powerful method for visualizing and comparing experimental designs and deriving appropriate models for their analysis. Manual calculations are provided for early examples, allowing the reader to follow the analyses in detail. More complex calculations rely on the statistical software R, but are easily transferable to other software.
Though there are few prerequisites for effectively using the book, previous exposure to basic statistical ideas and the software R would be advisable.
Authors and Affiliations
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Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland
Hans-Michael Kaltenbach
About the author
Bibliographic Information
Book Title: Statistical Design and Analysis of Biological Experiments
Authors: Hans-Michael Kaltenbach
Series Title: Statistics for Biology and Health
DOI: https://doi.org/10.1007/978-3-030-69641-2
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Nature Switzerland AG 2021
Hardcover ISBN: 978-3-030-69640-5Published: 16 April 2021
Softcover ISBN: 978-3-030-69643-6Published: 17 April 2022
eBook ISBN: 978-3-030-69641-2Published: 15 April 2021
Series ISSN: 1431-8776
Series E-ISSN: 2197-5671
Edition Number: 1
Number of Pages: XIV, 269
Number of Illustrations: 63 b/w illustrations, 7 illustrations in colour