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Biostatistical Analysis (4th Edition) By Jerrold H. Zar ( Prentice Hall )
Release Date: 1998-10-18
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List Price: $130.67
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Product Description
The latest edition of this best-selling biostatistics book is both comprehensive and easy to read. It provides a broad and practical overview of the statistical analysis methods used by researchers to collect, summarize, analyze, and draw conclusions from biological research data. The Fourth Edition can serve as either an introduction to the discipline for beginning students or a comprehensive procedural reference for today's practitioners.
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 great reference book for biostats
This book was required for a graduate course in biological statistics and it's been a great help. It will be a great book to refer to for many years to come in scientific research.
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excellent biostatistics text
This book is popular because it is well written and authoritative. It is written for biologists, medical students and researchers who do not have any prior knowledge of probability or statistics and may have little mathematical training as well. It serves as an introductory text providing many homework exercises. It can also be used as a reference. It is very thorough and covers most of the important topics required for biological problems. The needed probability is introduced when necessary.
There is the usual emphasis on hypothesis testing and regression. Correlation and analysis of variance are also very well covered. Important issues of sample size determination are covered and many solutions are provided in easy to use box descriptions.
As the author points out in the preface, in order to make this text a good reference it is extensive (663 pages of text followed by appendices and a large number of tables). It also includes a wealth of useful reference articles and books. Consequently, there is too much material for a one semester course. The author provides instructors with guidelines for sections to cover in an introductory course.
Notable topics covered in this text that is rarely found in introductory biostatistics books include multivariate methods especially the multivariate analysis of variance (MANOVA)and inference for circular data.
Recent developments in meta analysis, Bayesian statistics and bootstrap methods are not covered. In fact, these topics are not covered at all. Also, the important topic of missing data is omitted. Outliers are only covered briefly and just a few references are given but the major references, the texts by Hawkins and the treatise of Barnett and Lewis are neglected.
I am currently working on an elementary text that will have the advantage of some real world applications and modern developments. There are a few other elementary statistical texts for biology that are worth considering including Motulsky's "Intuitive Biostatistics" and
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Stats Bible!
This book is thought of as the "Statistics Bible" by the grad students at my school. This book is all a biologist will ever need for statistics reference.
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 Not for beginners
I own this book, which I purchased for a graduate-level statistics class. This book does include virtually everything you'd need as a biological statistician, but I have found most of it totally unaccessible. It's far too verbose which makes it difficult to plow through and I feel it's mostly obsolete since it makes no reference to computer software. Since statistics is now a field based almost exclusively on computer programs, a book based entirely on doing statistics by hand is not helpful! I'd say, save your $100 and look elsewhere (like the literature and an SPSS manual).
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More useful than other beginner's texts but... ( martin21890 )
As someone who recently retired from analyzing ecological data after a decade of it, I found this book to be pretty good one-stop shopping. I wouldn't say it's an introduction to stats so much as it is a systematic compilation of all the "traditional" statistical topics (t-tests, regressions, etc). As such, it contained some useful formulas that do not occur in regular "Stats 101" texts, such as sample size estimators for various analyses.
However, there are two things it is missing. As mentioned by other reviewers, there's no coverage (in the edition I have, anyway) of iterative techniques like bootstrapping, Monte Carlo approaches, etc. Those are coming up a lot in everyday statistical work these days.
More important is something missing from nearly EVERY beginning statistics text (and, often, from college education), which is the place of statistical testing in scientific logic. Too many beginners with statistics get stuck on fishing for significant differences in a stale old dataset rather than really thinking about their subject matter. In the absence of context, statistical "significance" can be deceptive and meaningless. One place to start on this subject is with Murphy & Myor's really good book called Statistical Power Analysis. I learned a ton from that book, which is a good companion for nearly any regular stats text. Happy crunching..
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