Monday, April 18, 2011

Primer of Biostatistics, Seventh Edition (Primer of Biostatistics (Glantz)(Paperback))

Primer of Biostatistics, Seventh Edition (Primer of Biostatistics (Glantz)(Paperback))

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Product Description

A concise, engagingly written introduction to understanding statistics as they apply to medicine and the life sciences

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CD-ROM performs 30 statistical tests</p></i>

Don't be afraid of biostatistics anymore! Primer of Biostatistics,7th Edition demystifies this challenging topic in an interesting and enjoyable manner that assumes no prior knowledge of the subject. Faster than you thought possible, you'll understand test selection and be able to evaluate biomedical statistics critically, knowledgeably, and confidently.
With Primer of Biostatistics, you’ll start with the basics, including analysis of variance and the t test, then advance to multiple comparison testing, contingency tables, regression, and more. Illustrative examples and challenging problems, culled from the recent biomedical literature, highlight the discussions throughout and help to foster a more intuitive approach to biostatistics.

The companion CD-ROM contains everything you need to run thirty statistical tests of your own data. Review questions and summaries in each chapter facilitate the learning process and help you gauge your comprehension. By combining whimsical studies of Martians and other planetary residents with actual papers from the biomedical literature, the author makes the subject fun and engaging.

Coverage includes:

  • How to summarize data
  • How to test for differences between groups
  • The t test
  • How to analyze rates and proportions
  • What does � not significant” really mean?
  • Confidence intervals
  • How to test for trends
  • Experiments when each subject receives more than one treatment
  • Alternatives to analysis of variance and the t test based on ranks
  • How to analyze survival data

Primer of Biostatistics, Seventh Edition (Primer of Biostatistics (Glantz)(Paperback)) Review

This book showed up in my med school library today and I read most of it in about an hour. Not that I'm anything special in terms of reading speed, it's just not as dense as most stat books. That's a good thing, mostly - the author has an engaging writing style that's approachable. He goes over a large number of statistical tests, applying them to problems such as predicting martian weights for a given height. Yep, Martians. And plotonians, when the tobacco companies are forced to market further afield. But he is pretty step-by-step which is good for an intro.

What is the standard deviation? When would you use a t-test? Why p < .05? If those are new concepts to you then I think you'd find it useful. He makes the point in his intro that many people just accept journal article results. Maybe that's his tie-in to biostats - if you are reading biostats articles then you need to know stats?

To me, if you're looking to learn about biostatistics, I say keep looking. While the author does use examples that relate to living things, such as the effect cell phone radiation on rabbit sperm, it's got very little to do with the business of biostatistics. He's got so many elements in there to let you calculate stats by hand (or to use programs that appear on the accompanying CD-ROM) that it fluffs up the book unnecessarily. Personally I'd just get a Schaum's outline which will give you the opportunity to practice the concepts and then an actual biostats book to learn more about the field. Or maybe get this book along with a schaum's guide so you'll at least be able to work with the concepts. Here's one I picked up - it's cheap. Schaum's Outline of Probability and Statistics, 3rd Ed. (Schaum's Outline Series)

So, high marks for readability, as an introductory stats book, but when you try to think about reality - when the relationships between what you are trying to predict and all of the things you hope predict that thing aren't perfect it shows that it's only 250 useful pages and in the end it's just what it says, a primer but of statistics, not biostatistics.

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