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New handbook for biologists who need more competence or confidence in statistics

COLD SPRING HARBOR, N.Y. (Jan. 5, 2010) -- New technologies such as microarrays, next-generation sequencing, and proteomics have dramatically increased the need for quantitative reasoning among biologists when designing experiments and interpreting results. Even the most routine informatics tools rely on statistical assumptions and methods that need to be appreciated if the scientific results are to be correct, understood, and exploited fully.

Statistics at the Bench: A Step-by-Step Handbook for Biologists, just released by Cold Spring Harbor Laboratory Press, is a convenient research companion for biologists who need to perform or interpret elementary and intermediate statistical analyses. Descriptions of statistical calculations are accompanied by commands for performing them in Excel, a software application familiar to biologists. This way, biologists can feel comfortable performing the tests themselves, without having to learn the complex commands and codes common in statistical software packages.

The book was written by Martina Bremer (San Jose State University) and Rebecca W. Doerge (Purdue University), both well-respected practitioners and teachers of statistics in biology. "Today, computationally trained biologists are gaining a competitive edge in science," Bremer and Doerge write in the introductory chapter. "Our purpose in providing this Manual is to assist biologists in becoming fluent and comfortable in the language of quantitative reasoning and to facilitate open and informed communication between the biological and the quantitative sciences."

The handbook is aimed at working biologists with little statistical or quantitative background, those who need a quick refresher, or those seeking a general overview of a statistical procedure. It describes statistical tests and calculations, commands for performing them in Excel, and guidelines for interpreting the results. Terms, concepts, and underlying principles are clearly explained, common pitfalls are discussed, and the methods are illustrated with examples of biological relevance.


Contact: Ingrid Benirschke
Cold Spring Harbor Laboratory

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