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hcistats:poweranalysis [2014/03/29 02:19]
Koji Yatani [Retrospective Power Analysis (not recommended)]
hcistats:poweranalysis [2014/03/29 02:20] (current)
Koji Yatani [Introduction]
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 =====Introduction===== =====Introduction=====
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 NHST can tell you how likely randomly sampled data would be like your data or even more extreme than it given that the null hypothesis (//e.g.//, there is no difference in the mean across the groups to compare) is true. As a standard threshold, we use 0.05, and we call this //alpha//. This means that if randomly sampled data can be like your data at lower than 5% change, you reject the null hypothesis (and claim that we observe a difference). Thus, if your p value is lower than //alpha//, we say that you have a significant result. NHST can tell you how likely randomly sampled data would be like your data or even more extreme than it given that the null hypothesis (//e.g.//, there is no difference in the mean across the groups to compare) is true. As a standard threshold, we use 0.05, and we call this //alpha//. This means that if randomly sampled data can be like your data at lower than 5% change, you reject the null hypothesis (and claim that we observe a difference). Thus, if your p value is lower than //alpha//, we say that you have a significant result.
  
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-^^Reject the null hypothesis^Fail to reject the null hypothesis^+^ ^Reject the null hypothesis^Fail to reject the null hypothesis^
 |The null hypothesis is true.|**Type I error** (false positive)|True negative| |The null hypothesis is true.|**Type I error** (false positive)|True negative|
 |The null hypothesis is false.|True positive|**Type II error** (false negative)| |The null hypothesis is false.|True positive|**Type II error** (false negative)|
hcistats/poweranalysis.txt ยท Last modified: 2014/03/29 02:20 by Koji Yatani