Significance levels: Difference between revisions
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[[Image:Tanabe08-fig3d.png|left|thumb|400px|Figure 3d from [http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.0060037 Tanabe et al. 2008] showing data sets that are deemed not significantly different (N.S.; >0.05) and data sets that are significant at different levels: * p<0.05, ** p<0.01, *** p<0.001]] | |||
==See also== | ==See also== | ||
==External links== | ==External links== | ||
Revision as of 08:46, 14 July 2009
The significance level is the criterion used for rejecting the null hypothesis.
Use as follows:
- determine the difference between the results of the experiment and the null hypothesis
- compare the probability of the null hypothesis to the significance level
If the probability is less than or equal to the significance level, then the null hypothesis is rejected and the outcome is said to be statistically significant.
Traditionally, researchers have used either the 0.05 level (5% level) or the 0.01 level (1% level), although the choice is largely subjective. The lower the significance level, the more conservative the statistical analysis and the more the data must diverge from the null hypothesis to be significant.
Star shorthand for significance levels
| star code | significance | comment |
|---|---|---|
| *** | 0.01 | high significance |
| ** | 0.05 | medium significance |
| * | 0.10 | low significance |
