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New book dissects statistics for doctors and medical students

COLD SPRING HARBOR, N.Y. (Oct. 21, 2008) The medical literature is chock full of risk ratios, P values, numbers needed to treat, life tables, regressions, survival analyses, and confidence intervals. But what do they mean?

A second edition of the book Medical Statistics Made Easy, recently released by Scion Publishing (, provides the easiest possible explanations of statistical tests and descriptions used throughout the medical literature. It will serve as an essential resource for medical students and professionals who need to understand common statistical terms.

"Whether you love or hate statistics, you need to have some understanding of the subject if you want to critically appraise a paper. To do this, you do not need to know how to do a statistical analysis. What you do need is to know why the test has been used and how to interpret the resulting figures," explain the authors, Michael Harris and Gordon Taylor, in the Preface to the book.

The "Statistics at work" section, which offers real-life examples from published papers, has been completely updated in this new edition. The new edition retains the user-friendly format of the first edition, with examples to illustrate concepts and clear explanations of how to interpret the results.

Each statistical test is presented with concise answers to the same series of questions, such as "How important is it?" "When is it used?" and "What does it mean?" To generate the answers to these questions, the authors compiled 200 recently published, mainstream medical papers and noted how frequently the statistical tests were used in each. They then developed a star system (1-5 stars) to rate the importance and usefulness of each statistical test or concept.

"Acquiring the skills to appraise medical research papers is a daunting task," writes Bill Irish in the Foreword to the book. "I commend this book to all healthcare professionals, general practitioners and hospital specialists. It covers all ground necessary to critically evaluate the statistical elements of research papers, in a friendly and approachable way."


Contact: Jane Carter
Cold Spring Harbor Laboratory

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