How is a Bonferroni correction performed?

The Bonferroni correction is a statistical method used to address the problem of multiple comparisons by adjusting the significance threshold to reduce the likelihood of obtaining false-positive results. It is particularly important in studies where multiple hypotheses are tested simultaneously, as each test increases the chance of incorrectly rejecting the null hypothesis due to random chance.

The Bonferroni correction is performed by dividing the critical P value by the number of comparisons being made. This means that if researchers are conducting multiple statistical tests, the significance level for each individual test is adjusted downward to maintain the overall error rate. For instance, if the conventional alpha level (significance level) is set at 0.05 and there are five comparisons, the Bonferroni adjusted significance level would be 0.05 / 5 = 0.01 for each test. This adjustment ensures that the cumulative probability of making one or more errors across all tests remains at the desired level, typically 0.05.

The other methods mentioned do not accurately define the Bonferroni correction process, as they do not involve adjusting the significance level in a manner that appropriately controls for the increase in error risk associated with multiple tests.