Which statement accurately describes Bonferroni correction regarding multiple testing?

• A. It reduces the chance of false positives
• B. It controls Type I error across multiple tests
• C. It increases the probability of Type II error only
• D. It does not affect error rates

Answer: (B)

Bonferroni correction is a method for handling multiple testing by controlling the probability of any false positive across a family of tests. When you run several statistical tests, the chance of at least one Type I error grows with the number of tests. The Bonferroni approach fixes this by dividing the overall significance level by the number of tests and using that smaller threshold for each test. For example, with five tests and an overall alpha of 0.05, you would test each hypothesis at 0.01. This keeps the familywise error rate—the probability of at least one false positive across all tests—at or below the chosen alpha. The trade-off is reduced power, since the stricter threshold makes it harder to detect real effects, increasing the risk of Type II errors, especially with many tests or small effects. So describing Bonferroni as controlling Type I error across multiple tests best captures its purpose.