Intuitive Biostatistics

By Harvey Motulsky

Book Overview

Designed to provide a nonmathematical introduction to biostatistics for medical and health science students, graduate students in the biological sciences, physicians, and researchers, this text explains statistical principles in non-technical language and focuses on explaining the proper scientific interpretation of statistical tests rather than on the mathematical logic of the tests themselves.
Intuitive Biostatistics covers all the topics typically found in an introductory statistics text, but with the emphasis on confidence intervals rather than P values, making it easier for students to understand both. Additionally, it introduces a broad range of topics left out of most other introductory texts but used frequently in biomedical publications, including survival curves. multiple comparisons, sensitivity and specificity of lab tests, Bayesian thinking, lod scores, and logistic, proportional hazards and nonlinear regression.
By emphasizing interpretation rather than calculation, this text provides a clear and virtually painless introduction to statistical principles for those students who will need to use statistics constantly in their work. In addition, its practical approach enables readers to understand the statistical results published in biological and medical journals.

• Format: Paperback
• Language: English
• ISBN: 0195086074
• ISBN13: 9780195086072
• Release Date: October 1995
• Publisher: Oxford University Press, USA
• Length: 408 Pages
• Weight: 1.30 lbs.
• Dimensions: 1.0" x 9.1" x 6.1"

Customer Reviews

A great non-technical introduction to biostatistics

I often recommend this book to two different groups: * colleagues who want to have a better understanding of the factors that drive statistical methods in medical research, without having to learn the actual statistics themselves and * students who are soon going to be taking biostatistics for the first time, and are anxious about whether they will be able to understand the material. For those who are a little on the math phobic side of things, this can be a great introduction to read through before formal coursework begins.

Excellent non-mathematical overview

Dr. Motulsky does an excellent job of introducing statistical concepts through examples and direct applications. Where this book is especially valuable is in keeping things simple -- without the intimidating mathematical notation -- while providing examples of where statistics can be used to measure the wrong things or present results that do not make sense in the context of what the researcher is investigating.My favorite example illustrates how a stastical analysis of a new test that identifies those susceptible to a fatal disease "shows" an increase in the average lifespan of both populations (those who suffer the disease and those who don't). The reality, of course, is no one is living longer because of the test, but rather the population sampled is different. Brilliant and concise.Although the text is targeted towards those in the bioinformatic and medical vocations, it's useful beyond that because the presentation of concepts is practical and yet without the notation.

This is a great book

I'm a practicing physician who has found it necessary to try to educate myself on the use of biostatistics in the medical literature. I have read over 20 books on biostatistics. This is clearly the best. It is written so that even the non-statistician can understand the concepts, and explains the statistical approach and rationale without scaring the reader away with arcane formulas. It is very logical in its progression and addresses the errors and assumptions that doctors make when trying to evaluate a paper. This book should be required reading not only by every medical student, but by anyone who attempts to write or interpret the medical literature.

Outstanding Biostatistics Book for the Non-statistician

I was delighted to discover this book four years ago, when I began teaching a course in clinical research methods. I have not seen anything else like the text or the optional companion software by GraphPad. The textbook is extremely well-written and well-organized. Not only have I been using the book and software in my teaching, but I have found that they handle about 90% of my own statistical needs for my research.The author's philosophy (to forget the fancy stuff since the vast majority of applications don't require it) and the way it is implemented (with just enough theory to protect users from making false inferences) are exactly right. Dr. Motulsky has done a a superb job.