Bonferroni Correction

The Bonferroni correction is a multiple-comparison correction used when several dependent or independent statistical tests are being performed simultaneously (since while a given alpha value alpha may be appropriate for each individual comparison, it is not for the set of all comparisons). In order to avoid a lot of spurious positives, the alpha value needs to be lowered to account for the number of comparisons being performed.

The simplest and most conservative approach is the Bonferroni correction, which sets the alpha value for the entire set of n comparisons equal to alpha by taking the alpha value for each comparison equal to alpha/n. Explicitly, given n tests T_i for hypotheses H_i (1<=i<=n) under the assumption H_0 that all hypotheses H_i are false, and if the individual test critical values are <=alpha/n, then the experiment-wide critical value is <=alpha. In equation form, if

 P(T_i passes |H_0)<=alpha/n

for 1<=i<=n, then

 P(some T_i passes |H_0)<=alpha,

which follows from the Bonferroni inequalities.

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