A type of multiple comparison test used in statistical analysis. When an experimenter performs enough tests, he or she will eventually end up with a result that shows statistical significance, even if there is none. If a particular test yields correct results 99% of the time, running 100 tests could lead to a false result somewhere in the mix. The Bonferroni test attempts to prevent data from incorrectly appearing to be statistically significant by lowering the alpha value.
The Bonferroni test, also known as the "Bonferroni correction" or "Bonferroni adjustment" suggests that the "p" value for each test must be equal to alpha divided by the number of tests.
The Bonferroni test is named for the Italian mathematician who developed it, Carlo Emilio Bonferroni (1892–1960). Other types of multiple comparison tests include Scheffe’s test and the Tukey-Kramer method test. A criticism of the Bonferroni test is that it is too conservative and may fail to catch some significant findings.