The Analysis of Biological Data by Michael C. Whitlock and Dolph Schluter introduces a new approach to teaching introductory statistics to biology students. Authors use several techniques to reach this unique audience. The authors' approach to teaching statistics truly makes the appropriate connections to the kinds of problems and data biological researchers will encounter today.
The book covers basic topics in introductory statistics, including graphs, confidence intervals, hypothesis testing, comparison of means, regression, and designing experiments. It also introduces the principles behind such modern topics as likelihood, linear models, meta-analysis and computer-intensive methods. Instructors and students consistently praise the book's clear and engaging writing, strong visualization techniques, and its variety of fascinating and relevant biological examples.
Throughout, they teach statistics in the context of interesting biological and medical examples; they emphasize intuitive understanding rather than an over-reliance on formulas; they focus on the data rather than the mathematical foundations of statistics; and they introduce - on a conceptual level - modern topics such as likelihood, regression, randomization, meta-analysis and the bootstrap.
This book provides an introduction to the use of modern statistical techniques for analyzing biological data, aimed at introductory and intermediate classes of biology students. The book uses hundreds of real, interesting biological examples to demonstrate these techniques.
Instructors and students consistently praise the book's clear and engaging writing, strong visualization techniques, and the wide variety of fascinating and relevant biological examples. I found the book engaging, intuitive, and with a coverage and pace that is perfect for a first statistics course for students in biology.
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