If only one statistical test is conducted, the Bonferroni correction is generally...

• A. Needed when multiple tests are performed
• B. Needed even for a single test
• C. Never needed
• D. Should be applied to data collection

Answer: (A)

Bonferroni correction is a way to control the chance of a false positive when you’re making several statistical comparisons. It works by lowering the alpha level for each individual test: you divide the overall significance threshold by the number of tests. Because of that, you only need this adjustment when you have multiple tests. If you’re conducting a single test, dividing alpha by one leaves it the same, so applying the correction changes nothing and isn’t needed in practice. That’s why the statement that it’s needed when multiple tests are performed is the best description of its purpose. The idea that it’s needed even for a single test is not accurate, and saying it should be applied to data collection misplaces the correction, which is a testing-level adjustment rather than a data-collection policy.