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The significance level is the pre-specified probability threshold, conventionally set at 0.05, used in hypothesis testing to decide whether a result is deemed statistically significant, and it is the probability of committing a type 1 error, that is, of wrongly rejecting a true null hypothesis. Setting it defines how strong the evidence against the null hypothesis must be before it is rejected, and choosing a lower level reduces the chance of a false positive at the cost of requiring stronger evidence. The conventional value is a pragmatic convention rather than a marker of importance, and where many hypotheses are tested the threshold may be adjusted to control the overall error rate. The significance level should not be confused with the clinical importance of a finding, which depends on effect size.

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