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Intuitive Biostatistics, First Edition Paperback – Oct 1 1995


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Product Details

  • Paperback: 408 pages
  • Publisher: Oxford University Press; 1 edition (Oct. 1 1995)
  • Language: English
  • ISBN-10: 0195086074
  • ISBN-13: 978-0195086072
  • Product Dimensions: 23.2 x 2.6 x 15.5 cm
  • Shipping Weight: 907 g
  • Average Customer Review: 4.9 out of 5 stars  See all reviews (14 customer reviews)
  • Amazon Bestsellers Rank: #597,771 in Books (See Top 100 in Books)
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Review

"I like this book much, I will be "beta-testing" it on my upper-level undergraduate biostatistics class. It fills a great need for my students."--Harriette Phelps, University of D.C.

"This splendid book meets a major need in public health, medicine, and biomedical research training--a user-friendly biostatistics text for non-mathematicians."--Gilbert S. Omenn, Executive Vice President for Medical Affairs at the University of Michigan

"Motulsky has written a very readable and delightful account of how statistics are used in biology and medicine...He focuses on clinical studies and covers a broad range of topics, including...such specialized areas as survival analysis, Bayesian inference, and logistic regression." --Quarterly Review of Biology

"The unique aspect of the book, which makes it different from other biostatistics books, is its approach to the content...His goal is to help the reader interpret medical literature rather than analyze a set of data....I higly recommend this book for those needing a non-mathematical, explanatory introduction to biostatistics. It is well-written and provides wonderful clinical examples and biostatistical content...An excellent resource book for medical students and housestaff who are struggling along with the concepts; and for those of you who were wondering, it was surprisingly easy to read."--Joseph Chu, MD, MPH, University of Washington in Teaching and Learning Medicine

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Format: Paperback
I'm doing my PhD and needed something to strengthen my basic biostatistics for the comprehensive exams and for my career (of course). I purchased this book because of the great reviews it has.

The strength:
It indeed deserves the five stars IF you are looking for a book to help you lay down a good stats foundation. Its main strengths are the explanation of the very basic concepts such as confidence intervals, P values, standard deviation, survival curves, relative risk, (a little of) odds ratio, clinical/screening tests, etc. To be honest, I only began to really understand and differentiate all these concepts after reading this book. It is very clear, easy to understand, and very repetitive (in a good way). Now I feel so more confident in interpreting research papers (with all those overwhelming P values) and stats outputs.

The weakness:
Motulsky spends a great deal of chapters explaining the basics I mentioned earlier. Therefore, if what you need is something on statistic tests such as ANOVA, MANOVA, regression, etc., this book wouldn't deserve five stars for you. Although it does try to explain how to interpret the output, the F value and alike, it is very, very superficial. In this case you would better off getting a more advanced statistics book.

But it definitely fitted my needs, so it does deserve five stars to me.
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Format: Paperback
A really nifty book for anyone--and that's most of us--interested in what basic statistical tests mean and how to use them. Even someone with a pretty advanced knowledge of statistics may not understand all of the intuitive concepts described in this book. Consistent with its title, it is probably best suited for those in the biosciences, rather than engineers, for example, but I'd say that people in those more technical fields may very well benefit greatly from reading it. It's written in a conversational manner that is easy to digest. I'd say a lot of thinking by the author went into creating it, because he seems to guess what the reader may be thinking and then answers those questions. He's big on the confidence interval, too. Readers who need more specialized, detailed info on a particular topic, such as two-way ANOVA, probably need to consult an additional text. Overall, a great introduction to fundamental statistical concepts and tests, that will be of interest to biological scientists and many other folks, too. Author of Adjust Your Brain: A Practical Theory for Maximizing Mental Health.
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Format: Paperback
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.
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Format: Paperback
Dr. Motulsky is an MD who is also a Professor of Pharmacology and President of his own software company. The book's title suggests that he can make biostatistics intuitive for non-statisticians (e.g. physicians, clinicians and nurses). After reading through it he has made a believer out of me! He introduces concepts through examples and touches on most of the important statistical methods that are used in the medical literature. While the book could be used as a classroom text, it seems to me to be more suited as a reference source for medical researchers who want to understand the statistics described in research papers. Although not a statistician by training, Dr. Motulsky has a good understanding of statistical methods and principles and exhibits his wisdom and experience throughout the book. He is deliberate at keeping things simple and to the point. He points out that he intentionally uses fake examples and modifies real examples for simplification of exposition. He avoids mathematics as much as possible. the preface and the introduction are very well written and the reader should read both before reading the rest of the text.
My usual concern with such books is that concepts are oversimplified and the presentation is too cook-bookish. Amazingly that is not the case here. Professor Motulsky carefully explains concepts such as confidence intervals, p-values, multiple comparison issues, Bayesian thinking and Bayesian controversy in a way that should be understandable to his intended audience.
Proportions and the binomial distribution are introduced early. Advanced topics such as sequential methods, survival curves and logistic regression are tackled. These subjects are important in medical research but are often avoided in elementary books.
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