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Power Analysis for Experimental Research: A Practical Guide for the Biological, Medical and Social..

By addebook • Jun 22nd, 2008 • Category: Biology Get in Amazon

Power Analysis for Experimental Research: A Practical Guide for the Biological, Medical and Social Sciences

By R. Barker Bausell, Yu-Fang Li,

Publisher: Cambridge University Press
Number Of Pages: 376
Publication Date: 2006-03-09
Sales Rank: 260762
ISBN / ASIN: 0521024560
EAN: 9780521024563
Binding: Paperback
Manufacturer: Cambridge University Press
Studio: Cambridge University Press


Power analysis is an essential tool for determining whether a statistically significant result can be expected in a scientific experiment prior to the experiment being performed. This comprehensive, accessible book provides practicing researchers with step-by-step instructions for conducting power/sample size analyses, assuming only basic prior knowledge of summary statistics and normal distribution. It contains a unified approach to statistical power analysis, with numerous easy-to-use tables that make further calculations or statistical expertise unnecessary.

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Power analysis is an essential tool for determining whether a statistically significant result can be expected in a scientific experiment prior to the experiment being performed. Many funding agencies and institutional review boards now require power analyses to be carried out before they will approve experiments, particularly where they involve the use of human subjects. This comprehensive, yet accessible, book provides practising researchers with step-by-step instructions for conducting power/sample size analyses, assuming only basic prior knowledge of summary statistics and the normal distribution. It contains a unified approach to statistical power analysis, with numerous easy-to-use tables to guide the reader without the need for further calculations or statistical expertise. This will be an indispensable text for researchers and graduates in the medical and biological sciences needing to apply power analysis in the design of their experiments.

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