Intuitive Biostatistics: a Nonmathematical Guide to Statistical Thinking, 2nd Revised Edition

Motulsky, Harvey

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ISBN 10: 0199730067 ISBN 13: 9780199730063
Published by Oxford University Press, 2010
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Synopsis:

THIS IS FOR THE 2nd EDITION. THE 3rd EDITION IS NOW AVAILABLE.
Overview
Intuitive Biostatistics is both an introduction and review of statistics. Compared to other books, it has:
  • Breadth rather than depth. It is a guidebook, not a cookbook.
  • Words rather than math. It has few equations.
  • Explanations rather than recipes. This book presents few details of statistical methods and only a few tables required to complete the calculations.
Who is it for?
I wrote Intuitive Biostatistics for three audiences:
  • Medical (and other) professionals who want to understand  the statistical portions of journals they read. These readers don't need to analyze any data, but need to understand analyses published by others.
  • Undergraduate and graduate students, post-docs and researchers who will analyze data. This book explains general principles of data analysis, but it won't teach you how to do statistical calculations or how to use any particular statistical program. 
  • Scientists who consult with statisticians. Statistics often seems like a foreign language, and this text can serve as a phrase book to bridge the gap  between scientists and statisticians.
What's new in the second edition?
Though the spirit of the first edition remains, very few of its words do. It is hard to explain what is new in this edition, since I essentially rewrote the entire book. New and expanded topics in the second edition of Intuitive Biostatistics include:
  • Chapter 1 explains how our intuitions can lead us astray in issues of probability and statistics.
  • Chapter 11 (and later examples) highlight the fact that lognormal distributions are common.
  • Chapter 21 explains the idea of testing for equivalence vs. testing for differences. 
  • Chapters 22, 23, and 40 discuss the pervasive problem of multiple comparisons. 
  • Chapters 24 and 25 discuss testing for normality and for outliers.
  • Chapter 35 shows how to think about statistical hypothesis testing as comparing the fits of alternative models.
  • Chapters 37 and 38 give expanded coverage of the usefulness--and traps--of multiple, logistic, and proportional hazards regression.
  • Chapter 43 briefly mentions adaptive study designs where sample size is not chosen in advance.
  • Chapter 46 (inspired by, and written with, Bill Greco) reviews many topics in this book and more general issues of how to approach data analysis.

About the Author: After graduating from medical school and doing an internship in internal medicine, I switched to research in receptor pharmacology (and published over 50 peer reviewed articles). While I was on the faculty of the Department of Pharmacology at the University of California San Diego, I was given the job of teaching statistics to first year medical students and to graduate students. The syllabus for those courses grew into the first edition of this book. I hated creating graphs by hand, so I created some programs to do so. I also created some simple statistics programs after realizing that the existing statistical software, while great for statisticians, was overkill for most scientists. These efforts were the origins of GraphPad Software Inc., which has been a full-time endeavor for many years. In this role I email with students and scientists almost daily, making me acutely aware of the many ways that statistical concepts can be confusing or misunderstood.

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Bibliographic Details

Title: Intuitive Biostatistics: a Nonmathematical ...
Publisher: Oxford University Press
Publication Date: 2010
Binding: paperback
Condition: Very Good
Edition: 2nd Edition

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Paperback. Condition: new. Paperback. Thoroughly revised and updated, the second edition of Intuitive Biostatistics retains and refines the core perspectives of the previous edition: a focus on how to interpret statistical results rather than on how to analyze data, minimal use of equations, and a detailed review of assumptions and common mistakes. Intuitive Biostatistics, Completely Revised Second Edition, provides a clear introduction to statistics for undergraduate and graduate students and also serves as a statistics refresher for working scientists. NEW TO THIS EDITION: * Chapter 1 shows how our intuitions lead us to misinterpret data, thus explaining the need for statistical rigor. * Chapter 11 explains the lognormal distribution, an essential topic omitted from many other statistics books. * Chapter 21 contrasts testing for equivalence with testing for differences. * Chapters 22, 23, and 40 explore the pervasive problem of multiple comparisons. * Chapters 24 and 25 review testing for normality and outliers. * Chapter 35 shows how statistical hypothesis testing can be understood as comparing the fits of alternative models.* Chapters 37 and 38 provide a brief introduction to multiple, logistic, and proportional hazards regression. * Chapter 46 reviews one example in great depth, reviewing numerous statistical concepts and identifying common mistakes. * Chapter 47 includes 49 multi-part problems, with answers fully discussed in Chapter 48. * New "Q and A" sections throughout the book review key concepts. Thoroughly revised and updated, the second edition of Intuitive Biostatistics retains and refines the core perspectives of the previous edition: a focus on how to interpret statistical results rather than on how to analyze data, minimal use of equations, and a detailed review of assumptions and common mistakes. Intuitive Biostatistics, Completely Revised Second Edition, provides a clear introduction to statistics for undergraduate and graduate students and also serves as a statistics refresher for working scientists. NEW TO THIS EDITION: Chapter 1 shows how our intuitions lead us to misinterpret data, thus explaining the need for statistical rigor.Chapter 11 explains the lognormal distribution, an essential topic omitted from many other statistics books.Chapter 21 contrasts testing for equivalence with testing for differences.Chapters 22, 23, and 40 explore the pervasive problem of multiple comparisons.Chapters 24 and 25 review testing for normality and outliers.Chapter 35 shows how statistical hypothesis testing can be understood as comparing the fits of alternative models.Chapters 37 and 38 provide a brief introduction to multiple, logistic, and proportional hazards regression.Chapter 46 reviews one example in great depth, reviewing numerous statistical concepts and identifying common mistakes.Chapter 47 includes 49 multi-part problems, with answers fully discussed in Chapter 48.New "Q and A" sections throughout the book review key concepts. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9780199730063

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