Biometry

by Robert R. Sokal and F. James Rohlf

Book Overview

Sokal and Rohlf's classic text deals with statistics from numerous areas of biological research, focusing on practical applications and incorporates computer calculations. This description may be from another edition of this product.

• Format: Hardcover
• Language: English
• ISBN: 0716724111
• ISBN13: 9780716724117
• Release Date: September 1994
• Publisher: W. H. Freeman
• Length: 88 Pages
• Weight: 1.75 lbs.
• Dimensions: 1.8" x 5.9" x 10.0"

Customer Reviews

good reference for bioinformatics applications

I have been using this book borrowed from someone else, and decided to buy it finally. It is a good book for people who know the basics of probability and statistics, and want to quickly look up applications for use in their work. The book covers a wide range of commonly used statistical tools and is fairly lucid in explaining their use, most of the time.

THE Biometry textbook of choice

I use this as a personal reference. Have examined many dozens of statistics books and this is the Bible, as far as I am concerned. It is clear, has excellent coverage, and is actually written engagingly! If you are going to have only one statistics book--it should be this one.

The Standard Introductory Textbook on Biostatistics

"Biometry" should be regarded - if it isn't already - as the standard practical guide to both parametric and nonparametric univariate biostatistics. Although it is aimed primarily for researchers and students in the biological sciences and medicine, there are ample practical examples which should be useful to those in psychology, sociology and other fields where knowledge of statistics and statistical methods is quite essential. I own a copy of the second edition, which I've had for more than two decades, regarding it as my "go-to" book if I have questions about various univariate statistical techniques. As another reviewer has noted, this book is especially strong in discussing nonparametric statistics. I might add too that it is quite good in discussing tests of significance related to Analysis of Variance (ANOVA) and simple linear regression. Much to their credit, the authors have written a superb text in clear, often concise, English that could be used as a self-teaching introductory guide for a practical understanding of univariate biostatistics. However, I will note that those interested in learning the theoretical foundations of the parametric and nonparametric univariate biostatistics covered in "Biometry" should consult another book which does emphasis these topics: Zarr's "Biostatistical Analysis", which I agree is a superb introductory text on theoretical biostatistics.

Excellent basic text of statistical methods

This book and BIOSTATISTICAL ANALYSIS by Jerrold Zar are my main "go to" books when I have questions about statistical methods, applications, or interpretation. Zar's book is probably the more understandable primer text on statistics of the two, but BIOMETRY is better at addressing non-parametrics, though it is certainly not a comprehensive treatment of that field of statistical analysis.I typically go to Zar first, then to Sokal and Rohlf -- a great one-two combination that takes care of most of my statistical needs. I appreciate the inside covers of BIOMETRY, with its summary table that provides a starting place for choosing the most likely statistical tests for a give comination of numbers of samples and numbers of variables in an experiment.You should be advised that the book BIOMETRY does not contain tables of critical values. You will need to purchase the book STATISTICAL TABLES by Rohlf and Sokal to get them. All in all, an excellent book on statistical methods.4.5 to 5 stars...I'll give it 5 stars.Alan Holyoak

A timeless classic in statistical thinking

Although many students and educators now learn about statistics by using plug-n-play statistics packages like SAS or SPSS, a basic understanding of even the most fundamental statistical principles is essential to sound statistical reasoning. _Biometry_ is a wonderful introduction to statistics. Although designed for ecologists and evolutionary biologists, and although most of the examples are from the life sciences, it is an excellent introduction to statistical reasoning for anyone in any field. I would highly recommend this book, a title on Exploratory Data Analysis, and hands-on experience with a statistical package as the ideal introduction to statistics.