Statistical design and analysis of biological experiments / Hans-Michael Kaltenbach.
Kaltenbach, Hans-Michael, author.
2021
QH316.5
Available Online

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Title Statistical design and analysis of biological experiments / Hans-Michael Kaltenbach.
Author Kaltenbach, Hans-Michael, author.
ISBN 9783030696412 (electronic bk.)
3030696413 (electronic bk.)
9783030696405
3030696405
DOI https://doi.org/10.1007/978-3-030-69641-2
Published Cham : Springer, [2021]
Language English
Description 1 online resource
Other Standard Identifiers 10.1007/978-3-030-69641-2 doi
Call Number QH316.5
Dewey Decimal Classification 570.72/7
Summary 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.
Bibliography, etc. Note Includes bibliographical references and index.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed April 22, 2021).
Series Statistics for biology and health. 1431-8776
Available in Other Form Statistical design and analysis of biological experiments.
Linked Resources Online Access
Record Appears in Online Resources > Ebooks
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Principles of Experimental Design
Review of Statistical Concepts
Planning for Precision and Power
Comparing More than Two Groups
Comparing Treatment Groups with Linear Contrasts
Multiple Treatment Factors: Factorial Designs
Improving Precision and Power: Blocked Designs
Split-Unit Designs
Many Treatment Factors: Fractional Factorial Designs
Experimental Optimization with Response Surface Methods
References
Index.

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