Biometry: the principles and practice of statistics in biological research

Now in its fourth edition (published September 2012), this text has become the classic text on the application of statistics to biology since its initial publication in 1969.

The complete reference is:

Sokal, R. R. and F. J. Rohlf. 2012. Biometry: the principles and practice of statistics in biological research. 4th edition. W. H. Freeman and Co.: New York. 937 pp.
ISBN: 0-7167-8604-4 or 978-0-7167-8604-7.

New to this edition

An Increased Focus on Computer-Based Statistical Methods.  The authors have continued to recast most of their popular boxes to use computational formulas used in the latest computer based statistical methods.  These boxes demonstrate how the methods are used to solve key biometric problems and serve as brief summaries of the techniques discussed in the chapter.  Computational formulas have also been replaced throughout with simpler structural formulas for ease of understanding. Topics covered in the new computational boxes include 

• Testing of statistical hypotheses is introduced using permutation tests. Jackknife and bootstrap methods are also introduced.
• Meta-analysis (CH 18)

Matrix methods. Matrix methods are introduced in new sections on multiple regression, general linear models, ancova, and curvilinear regression. A new appendix on matrix algebra is also included

New Chapter on Statistical Power and Sample Size Estimation.  The new edition features a new chapter that covers statistical power, measures of effect size, and the estimation of sample size required for a test.  It includes methods for constructing confidence intervals of effect sizes  making use of the non-central t- and F-distributions. There is also a new sectionon problems with post-hoc power analyses.
 
Up-to-Date Coverage of Key Developments in Biostatistics.   This edition includes the most up-to-date coverage of key topics and trends in the discipline.  New topic coverage includes: 

• Recent developments in computing hardware and software (CH 3) 
• New chapter on statistical power and sample size in the analysis of variance (CH 12) and new sections on effect size, power, and sample size (CH 14, 15, 16, and 17)
• Dunnett’s test for comparing treatment means against a control is now included (CH9)
• Expanded coverage of model II regression (CH 14). 
• Multiple comparisons among cell means in a two-way ANOVA when interaction is present (CH 12)Coverage of the most recent methods for the estimation of variance components and their confidence intervals (CH 9).
• Path analysis coverage has been extended to include structural equation modeling (CH 16)
• New coverage of the use of the Akaike’s information criterion and related criteria for fitting complex models (CH 16)
• An updated version of the Kolmogorov-Smirnov test for comparing frequency distribution is included.
• Major new section on meta-analysis (CH 18)
• The Shapiro-Wilk test for normality and Levene's test for homogeneity of variances are now included (CH13)

Statistical tables