Encyclopedia of Systems Biology

2013 Edition
| Editors: Werner Dubitzky, Olaf Wolkenhauer, Kwang-Hyun Cho, Hiroki Yokota

Power and Sample Size

Reference work entry
DOI: https://doi.org/10.1007/978-1-4419-9863-7_1192

Definition and Characteristics

In statistical hypothesis testing, the power of the test refers to (1−β), where β is the probability of not rejecting the null hypothesis when it is false. Another component of the statistical comparison is the type I error α which gives the probability of rejecting the null hypothesis when it is true. The preferable analysis method is the one with small error and large power. The sample size and the power of the analysis are closely related and the larger the sample size, the more powerful the testing procedure is.

To design the study, one has to formulate the hypothesis, determine the appropriate testing procedure, set the desired error rate and the power, and estimate the appropriate sample size. In certain types of observational studies or when analyzing previously collected data, the calculations are reversed and power of the test is determined based on the data size.

Comparing the two population means μ 0 and μ 1against two sided alternative leads...
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References

  1. Van Belle G (2008) Chapter 2. In: Statistical rules of thumb, 2nd edn. Wiley, Hoboken, NJGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2013

Authors and Affiliations

  1. 1.Bioinformatics and High-throughput Analysis LaboratorySeattle Children’s Research InstituteSeattleUSA