Principles of Experimental Design for the Life Sciences

Murray R Selwyn Statistics Unlimited Inc., Wellesley, MA

List Price: $84.95
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Cat. #: 9461 ISBN: 0849394619 Publication Date: 5/23/1996 Number of Pages: 176

Let this down-to-earth book be your guide to the statistical integrity of your work. Without relying on the detailed and complex mathematical explanations found in many other statistical texts, Principles of Experimental Design for the Life Sciences teaches how to design, conduct, and interpret top-notch life science studies.

Learn about the planning of biomedical studies, the principles of statistical design, sample size estimation, common designs in biological experiments, sequential clinical trials, high dimensional designs and process optimization, and the correspondence between objectives, design, and analysis. Each of these important topics is presented in an understandable and non-technical manner, free of statistical jargon and formulas.

Written by a biostatistical consultant with 25 years of experience, Principles of Experimental Design for the Life Sciences is filled with real-life examples from the author's work that you can quickly and easily apply to your own. These examples illustrate the main concepts of experimental design and cover a broad range of application areas in both clinical and nonclinical research. With this one innovative, helpful book you can improve your understanding of statistics, enhance your confidence in your results, and, at long last, shake off those statistical shackles!

• Presents clear and comprehensive explanations of the advantages and disadvantages of common experimental designs
• Fully describes the experimental planning process, including generation of study objectives and writing of the experimental protocol
• Clearly explains the concepts of bias and variability, as well as methods to identify and control their sources
• Presents information on methods of data analysis, highlighting the author's unique "one-to-one-to-one" correspondence approach
• Includes two useful appendices: one on statistical terms and one on formulas for sample size estimation