Bonferroni Adjustment:
Bonferroni adjustment is used in multiple comparison procedures to calculate an adjusted probability a of comparisonwise type I error from the desired probability a_{FW0} of familywise type I error. The calculation guarantees that the use of the adjusted a in pairwise comparisons keeps the actual probability a_{FW} of familywise type I errors not higher than the desired level, as specified by the significance level of the test.
Bonferroni, an Italian mathematician, proved the following inequality:

for any value C. Since a_{FW} and a are linked by the formula

(see Familywise Type I Error), where C is the total number of pairwise comparisons, the Bonferroni inequality gives the following approximate formula

Suppose 4 populations are to be compared, and the maximum allowed familywise type I error is a_{FW0} = 0.05. Then, the total number of pairs C=4(41)/2=6, and Bonferroni adjustment gives a = 0.05/6 ? 0.0083. Now we may be sure that, if all the 4 populations have the same mean, and we test pairwise differences at significance level a = 0.0083, the probability a_{FW} that you will erroneously conclude that the population means in at least one pair differ is not higher than 0.05.
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