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Overview
Although few physicians, nurses, dentists, and other health professionals perform laboratory tests themselves, they all need to be able to interpret the results as well as understand findings reported in the medical literature. A general understanding of probability and statistics is essential for those needing to make daily decisions about the significance of research data, drug interaction precautions, or a patient's positive laboratory test for a rare disease.
Written with these needs in mind, Probability without Equations offers a thorough explanation of the subject without overwhelming the reader with equations and footnotes. Award-winning teacher Bart Holland presents a nontechnical treatment of intuitive concepts and presents numerous examples from medical research and practice. In plain language, this book explains the topics that clinicians need to understand:
• Analysis of variance
• "P-values" and the "t-test"
• Hazard models
• Regression and correlations
• Alpha and beta errors
"The Nobel prize-winning physicist Ernest Rutherford was fond of saying that if you need statistics to analyze the results of an experiment, you don't have a very good experiment. In a way he was right. However, a recurrent problem in medicine is that in a certain sense you commonly don't have a good experiment—but not because medical research scientists are generally incompetent! The nature of the data they work with is simply not as predictable as the data in some other fields, so the predictive nature of findings in medical science is generally rather imperfect."—from the introduction
The Johns Hopkins University Press
Appropriate for: Physicians and Nurses, Allied Health Professionals.
Synopsis
"A good primer for the initiated or those requiring a refresher... Highly recommended for those requiring a brief, general overview of the subject." — Doody's Book Review Service
Doody Review Services
Reviewer:Lou Fintor, MA, MPH(McGill University)
Description:This is an attempt to impart a general understanding of statistical probability as applied in the medical literature and in everyday practice. It is a simple, portable paperback of 113 pages including an introduction, list of books for additional reading, and index. The author, an award-winning associate professor at the New Jersey Medical School, has extensive experience in the design and analysis of clinical trials and has worked as a statistical consultant.
Purpose:According to the author, this book is designed to "make the language of the probabilist and statistician accessible." The author attempts "in plain language" to describe and explain the application and interpretation of these concepts in the medical literature.
Audience:The author suggests that the primary audience is physicians and other clinicians, but this book would also be quite useful for medical students, nurses, allied health professionals, and others who desire a fundamental, applied overview of probability and statistics as they are applied in medicine.
Features:This is a straightforward, concise approach to understanding often complex subject matter. The author has minimized the extensive use of mathematical formulas and theoretical constructs so common in this genre in favor of appealing to a broad audience, assuming relatively little experience with probability theory. Instead, these concepts are illustrated with pertinent examples drawn from the medical literature and everyday practice. The flow is logical and information is presented in a cumulative way. The illustrations are basic but adequate and appropriate. At the outset the author clearly defines common terms encountered in the literature and used in the book -- a nice touch.
Assessment:This book covers the basics: tests of statistical significance; sensitivity, specificity, and predictive value of clinical tests; epidemiologic research designs (including case-control, cohort, and cross-sectional studies); common clinical trial designs; and common statistical tests often encountered in the literature (t-tests, ANOVA, hazards models, and so forth). It is a good primer for the initiated or those requiring a refresher. At the same time, its brevity necessarily oversimplifies concepts and leads the reader to more thorough published treatments of the subject. The price seems somewhat steep for what the book delivers, but is in fact consistent with other recent publications in this genre. It is highly recommended for those requiring a brief, general overview of applied statistical probability.
Editorials
From The Critics
Reviewer: Lou Fintor, MA, MPH(McGill University)Description: This is an attempt to impart a general understanding of statistical probability as applied in the medical literature and in everyday practice. It is a simple, portable paperback of 113 pages including an introduction, list of books for additional reading, and index. The author, an award-winning associate professor at the New Jersey Medical School, has extensive experience in the design and analysis of clinical trials and has worked as a statistical consultant.
Purpose: According to the author, this book is designed to "make the language of the probabilist and statistician accessible." The author attempts "in plain language" to describe and explain the application and interpretation of these concepts in the medical literature.
Audience: The author suggests that the primary audience is physicians and other clinicians, but this book would also be quite useful for medical students, nurses, allied health professionals, and others who desire a fundamental, applied overview of probability and statistics as they are applied in medicine.
Features: This is a straightforward, concise approach to understanding often complex subject matter. The author has minimized the extensive use of mathematical formulas and theoretical constructs so common in this genre in favor of appealing to a broad audience, assuming relatively little experience with probability theory. Instead, these concepts are illustrated with pertinent examples drawn from the medical literature and everyday practice. The flow is logical and information is presented in a cumulative way. The illustrations are basic but adequate and appropriate. At the outset the author clearly defines common terms encountered in the literature and used in the book — a nice touch.
Assessment: This book covers the basics: tests of statistical significance; sensitivity, specificity, and predictive value of clinical tests; epidemiologic research designs (including case-control, cohort, and cross-sectional studies); common clinical trial designs; and common statistical tests often encountered in the literature (t-tests, ANOVA, hazards models, and so forth). It is a good primer for the initiated or those requiring a refresher. At the same time, its brevity necessarily oversimplifies concepts and leads the reader to more thorough published treatments of the subject. The price seems somewhat steep for what the book delivers, but is in fact consistent with other recent publications in this genre. It is highly recommended for those requiring a brief, general overview of applied statistical probability.