Experimental Design and Statistical Analysis for Pharmacology and the Biomedical Sciences is an invaluable reference and guide for undergraduate a nd graduate students, post-doctporal researchers and lecturers in pharmacology and allied subjects in the life sciences.
Dr Paul J. Mitchell is Senior Lecturer and Associate Professor in the Department of Life Sciences (Pharmacology group), University of Bath, UK, and Adjunct Lecturer in the Department of Pharmacology and Therapeutics, University of Galway, Ireland. He has more than 45 years experience in experimental pharmacology, experimental design, and statistical analysis. For the last 25 years Dr Mitchell has collaborated with colleagues to develop a coherent strategy to teach experimental design and statistical analysis to undergraduate and graduate students across subject areas.
Experimental Design and Statistical Analysis for Pharmacology and the Biomedical Sciences, 2022, pub Wiley, ISBN 978-1-119-43763-5, is available through Wiley, Waterstones, Amazon and all good book stores.
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Amazon, Feb 2023. One of the best statistics books I've seen.
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Experimental Design and Statistical Analysis for Pharmacology and the Biomedical Sciences
A practical guide to the use of basic principles of experimental design and statistical analysis in pharmacology
Experimental Design and Statistical Analysis for Pharmacology and the Biomedical Sciences provides clear instructions on applying statistical analysis techniques to pharmacological data. Written by an experimental pharmacologist with decades of experiences teaching statistics and designing preclinical experiments, this reader-friendly volume explains the variety of statistical tests that researchers require to analyse data and draw conclusions.
Detailed, yet accessible, chapters explain how to determine the appropriate statistical tool for particular type of data, run the statistical test, and analyse and interpret the results. By first introducing basic principles of experimental design and statistical analysis, the author then guides readers through descriptive and inferential statistics, analysis of variance, correlation and regression analysis, general linear modelling, and more. Lastly, throughout the textbook are numerous examples from molecular, cellular, in vitro and in vivo pharmacology which highlight the importance of rigorous statistical analysis in real-world pharmacological and biomedical research.
This textbook also:
- Describes the rigorous statistical approach need for publication in scientific journals,
- Covers a wide range of statistical concepts and methods, such as standard normal distribution, data confidence intervals, and post hoc and a priori analysis,
- Discusses practical aspects of data collection, identification and presentation,
- Features images of the output from common statistical packages, including GraphPad Prism, InVivo Stat, MiniTab and SPSS,
- Includes 24 chapters with 55 data sets (including 72 figures, 178 tables and 215 fully worked and resolved equations), 13 appendices (6 devoted to the probability density function of statistical distributions, AUC values according to Standard Normal probabilities and 6 devoted to the critical values of statistical distributions where p = 0.05, 0.01 and 0.001) and 4 decision flowcharts.
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