The Bonferroni correction is a method for adjusting alpha (α) across a set of significance tests where α is the probability of making a Type I error. A Type I error is the probability of rejecting the null hypothesis when the null hypothesis is actually true within the population. For a single significance test, a researcher sets an α-level representing the risk the researcher will reject the null hypotheses when the null is true. In practical terms, this risk is the chance a researcher might say two variables are correlated or there is some difference between two groups when in fact no correlation or difference exists. If α is set at p < .05 then there is a 5% chance for that test ...
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