© 2010 • 167 pp., illus., indexes
Concealed wire binding • £39.00 27.30 • ISBN  978-0-879698-57-7
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Statistics at the Bench is a convenient bench-side companion for biologists, designed as a handy reference guide for elementary and intermediate statistical analyses. The expectations for biologists to have a more complete understanding of statistics are growing rapidly. New technologies and new areas of science, 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.

This book is not a textbook. It is an essential handbook for working scientists. Statistics at the Bench provides a simple refresher for those who have forgotten what they once knew, and an overview for those wishing to use more quantitative reasoning in their research. Statistical methods, as well as guidelines for the interpretation of results, are explained using simple examples. Throughout the book, examples are accompanied by detailed Excel commands for easy reference.

  “Readers without access to statistical analysis software (or who prefer more user-friendly programs) will appreciate the detailed instructions about how to perform tests in Microsoft Excel. The authors also explain some methods that are beyond Excel’s capabilities, such as permutation tests and statistical classification methods, for researchers who want to take the next step... The book is published as a hardcover ring binder that lies flat on a desktop at any selected page, which is a nice touch that adds convenience...[T]he authors do a very good job of explaining the underlying concepts.”
      —Nature Neuroscience

  “The book is wire bound so that it will be convenient to keep open on the laboratory bench...it is intended as a handy quick refresher for methods that one may have learned some time ago. There are numerous small worked examples throughout the book. For such a short volume, it contains a surprising amount of detail about different types of clustering.”
      —The Quarterly Review of Biology

1. Introduction

2. Common Pitfalls

3. Descriptive Statistics

4. Design of Experiments

5. Confidence Intervals

6. Hypothesis Testing

7. Regression and ANOVA

8. Special Topics

References

Index of Worked Out Examples

Index of Excel Commands