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Biostatistical Analysis (Prentice-Hall biological sciences series)

4.3 out of 5 stars 47 customer reviews
ISBN-13: 978-0130769848
ISBN-10: 0130769843
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Editorial Reviews

From Library Journal

This book combines useful explanations of statistical methods in the biological sciences with statistical graphs and tables frequently employed by researchers. It requires no previous knowledge of statistics and can be used as a reference tool for those looking for information on population sampling, frequency analysis, probabilities, and more.
Copyright 1999 Reed Business Information, Inc. --This text refers to an out of print or unavailable edition of this title.

From the Publisher

This long-awaited revision of this best-selling biostatistics text is both comprehensive and easy to read. 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. --This text refers to an out of print or unavailable edition of this title.
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Product Details

  • Series: Prentice-Hall biological sciences series
  • Hardcover: 620 pages
  • Publisher: Prentice Hall (1974)
  • Language: English
  • ISBN-10: 0130769843
  • ISBN-13: 978-0130769848
  • Product Dimensions: 9.4 x 7.1 x 1.5 inches
  • Shipping Weight: 2.4 pounds
  • Average Customer Review: 4.3 out of 5 stars  See all reviews (47 customer reviews)
  • Amazon Best Sellers Rank: #5,067,259 in Books (See Top 100 in Books)

Customer Reviews

Top Customer Reviews

Format: Hardcover
This book and BIOMETRY by Sokal and Rohlf are the two standard statistics books that live on the shelves of most biological researchers.
Zar makes methods and interpretations of statistical analyses accessible and understandable. There are suffient numbers of statistical tests in the text to cover most of my statistical needs. The book also includes its own tables of critical values (something that BIOMETRY does not -- there's a paperback companion book of tables for that book). Zar also includes examples that are easy to follow, as well as enough mathematical background to allow one to understand the hypothetical and much of the mathematics behind the statistical methods.
I typically turn to Zar first when I have a statistical question. This book continues to be a highly prized ally of mine in the data analysis game.
I highly recommend this book to all biology grad students and researchers. It's well worth the price -- an investment that pays off!
5 stars, no doubt about it.
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Format: Hardcover
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.
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Format: Hardcover
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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Format: Hardcover
This textbook covers a very broad spectrum of biostatistics. It is the best reference for design and analysis of experiments, regardless of the application. This opinion is coming from a person with an MS in statistics. -Brian Mayeux statistician for NIOSH (CDC).
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Format: Hardcover Verified Purchase
I have found this book more approachable and user friendly than Sokal and Rohlf. Zar is an excellent desk reference, and has solved a number of statistical problems for me. I reccomend it to anybody who regularly uses statistics in a biological context.
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Format: Hardcover Verified Purchase
Supplier: Prompt and received well ahead of schedule!

Book: This is a classic. Some stated that it was high level, but I didn't see it that way. He provides great examples with good details on the exact calculations. One should be able to perform all calculations with any usual calculator or spreadsheet. He does not delve into any derivations or higher level math such as derivatives and integrals. In fact, the entire book is very practical.

This book covers from Biostatistics approach which means that there is more dealing with the nonparametric side and more dealing with metrics for species, diseases, etc. not usually found in statistical texts. He covers that same areas as the usual texts, but adds better examples, detail calculations and includes good interpretations. The emphasis was more on "use" rather than subtle statistical basics for the methods.

One of the great features was inclusion of Circular Statistics, which to date his is the only one I've come across that actually provides great coverage of this area. This is not covered in any texts that I've owned, except the original works by Mardia. And the examples are very good in how to use and applications. This area is surprisingly encountered more often than not and is always overlooked. I would buy this book just for that section alone. In fact this approach solves a lot of those periodic, seasonal variation problems I ran across in industry.

Overall, he covers the usual stats, adds a lot of features (similarity, diversity, various indices, etc.), covers "random", added chapters on circular, added "intraclass correlation" which is also overlooked, and still covers the basic stats that all need to know.
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