What typically sets the threshold for rejecting the null hypothesis in significance testing?

In significance testing, the threshold for rejecting the null hypothesis is often set at 0.05, which is a commonly used significance level in many fields of research. This means that if the p-value obtained from the test is less than 0.05, the results are considered statistically significant, leading researchers to reject the null hypothesis in favor of the alternative hypothesis. Setting this threshold provides a balance between the risk of making a Type I error (incorrectly rejecting a true null hypothesis) and Type II error (failing to reject a false null hypothesis).

Choosing 0.05 has become a widely accepted convention because it allows researchers a reasonable envelope of confidence while still remaining sensitive to the possibility of detecting meaningful effects or differences when they exist. Although other levels such as 0.01 or 0.10 can also be used in specific cases, 0.05 remains a standard benchmark in many scientific disciplines for determining significance.