Hypothesis Testing and Statistical Power of a Test
dc.altmetrics.display | false | en |
dc.contributor.author | Park, Hun Myoung | |
dc.date.accessioned | 2015-03-25T19:24:58Z | |
dc.date.available | 2015-03-25T19:24:58Z | |
dc.description.abstract | How powerful is my study (test)? How many observations do I need to have for what I want to get from the study? You may want to know statistical power of a test to detect a meaningful effect, given sample size, test size (significance level), and standardized effect size. You may also want to determine the minimum sample size required to get a significant result, given statistical power, test size, and standardized effect size. These analyses examine the sensitivity of statistical power and sample size to other components, enabling researchers to efficiently use research resources. This document summarizes basics of hypothesis testing and statistic power analysis, and then illustrates how to do using SAS 9, Stata 10, G*Power 3. | en |
dc.identifier.uri | https://hdl.handle.net/2022/19738 | |
dc.rights | Copyright 2015 by the Trustees of Indiana University. This content is released under the Creative Commons Attribution 3.0 Unported license (http://creativecommons.org/licenses/by/3.0/). | en |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/ | en |
dc.subject | statistical power analysis, hypothesis testing, ANOVA | en |
dc.title | Hypothesis Testing and Statistical Power of a Test | en |
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