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since they are multiplicative |
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'''1 - (1 - α)<sup>1/n</sup> = α''' (corrected for n comparisons)
For example, to test two independent hypotheses on the same data at 0.05 significance level, instead of using a [[p-value|''p'' value]] threshold of 0.05, one would use a stricter threshold of 0.
The Bonferroni correction is a safeguard against multiple tests of statistical significance on the same data falsely giving the appearance of significance, as 1 out of every 20 hypothesis-tests is expected to be significant at the α = 0.05 level purely due to chance. Furthermore, the probability of getting a significant result with ''n'' tests at this level of significance is 1-0.95<sup>n</sup> (1-probability of not getting a significant result with ''n'' tests).
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