Sunday, May 17, 2009

Primer of Biostatistics, 6/e 2005

Publisher: McGraw-Hill Medical
Number Of Pages: 500
Publication Date: 2005-04-15
Sales Rank: 154969
ISBN / ASIN: 0071435093
EAN: 9780071435093
Binding: Paperback
Manufacturer: McGraw-Hill Medical
Studio: McGraw-Hill Medical
Average Rating: 4
Extremely popular, this student-friendly text presents the practical areas of statistics in terms of their relevance to medicine and the life sciences. Includes many illustrative examples and challenging problems that reinforce the author��s unique and intuitive approach to the subject. The new edition features a new two-color design, examples taken from current biomedical literature, and review questions within each chapter. Review: Best stats book out there without the errors of the 6th edition The quickest, most accurate stats book out there. Warning: you must read it carefully, you can't really skim. That said, if you do read it carefully, even just the first few chapters, you will truly understand basic stats. Before reading this I didn't get significance or what a t-test really meant. Now I can speak the lingo and critically assess other authors work. Just a great book if you give it a few hours to sink in.
Get the 5th edition, not the 6th, for some reason the 6th is full of typos and errors in the examples. Review: good material, too many errors It's a decent book overall. The material is not too hard to underestand, and there are a lot of medical examples. However, there's nearly a typo on every other page. I wouldn't mind if the mistakes were minor, but it's too much when a third of the solutions are wrong, and statistical tables are incorrect (e.g. 6-8 & 6-9). Review: Non-mathematical introduction to biostatistics This is not a treatise in mathematics. The author uses easy to understand examples to explain concepts. Other reviewers have noted typos that altered their learning experience; I have not. Other reviewers report that the presentation of ANOVA is not easily understood; I disagree. Statisticians that are used to the Fisher and Scheff�� methods of explaining ANOVA will clearly find this different. I actually found it useful to present ANOVA before the T-test and to use the examples he did. Glantz's text on regression and ANOVA is also very good.
Review: Lots of mistakes in this book The concept of this book is good-cut to the chase and give lots of relevent examples. However, the book has innumerable typos which can make it very dificult to follow the text. Some sections are just incomprehensible such as the section on power calculations for the chi square test. Most of the exercises at the end of the chapter are heavy on arithmetic and light on conceptual issues. Often the answers to the exercises are wrong. All these typos are really unacceptable for a fifth edition. I am at Amazon looking for another text to keep as a reference. By way of disclaimer, I am taking

the author's course on introductory biostatistics and am doing average.

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