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Biostatistical Analysis (4th Edition) Hardcover – October 18, 1998

ISBN-13: 978-0130815422 ISBN-10: 013081542X Edition: 4th

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Product Details

  • Hardcover: 929 pages
  • Publisher: Prentice Hall; 4 edition (October 18, 1998)
  • Language: English
  • ISBN-10: 013081542X
  • ISBN-13: 978-0130815422
  • Product Dimensions: 7.1 x 1.6 x 9.3 inches
  • Shipping Weight: 3.3 pounds
  • Average Customer Review: 4.1 out of 5 stars  See all reviews (42 customer reviews)
  • Amazon Best Sellers Rank: #343,108 in Books (See Top 100 in Books)

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.

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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Customer Reviews

Supplier: Prompt and received well ahead of schedule!
dd1804
This book and BIOMETRY by Sokal and Rohlf are the two standard statistics books that live on the shelves of most biological researchers.
Alan R. Holyoak
It's easy to understand, offers plenty of examples, and relates concepts to real world examples well.
J.H.Niles

Most Helpful Customer Reviews

58 of 58 people found the following review helpful By Alan R. Holyoak on May 22, 2000
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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37 of 37 people found the following review helpful By Michael R. Chernick on February 7, 2008
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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15 of 16 people found the following review helpful By A Customer on February 24, 1999
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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13 of 14 people found the following review helpful By Chowderhead on July 16, 2006
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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8 of 8 people found the following review helpful By Robert B. Page on February 9, 2004
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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7 of 7 people found the following review helpful By A Customer on June 15, 1997
Format: Hardcover
The author knows the difficulties found by researchers when they need to analyse their data.
He writes about all topics of statistical analysis in a very simple way, and the solved examples makes our understanding smooth.
He knows how to drive us in such a way that analyzing biomedical data becomes compreehensible and easy! A book that biologists and people from the biomedical area must consult everyday! This book should be translated to other languages so much more people could learn from it!

Lucia M. Singer, M.Sc. Ph.D.
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