What is the purpose of adjusting significance and confidence levels?

• A. To meet regulatory submission requirements
• B. To control the overall Type I error rate when performing multiple analyses
• C. To increase statistical power of a single test
• D. To simplify interpretation of results

Answer: (B)

When you perform multiple analyses, the chance of finding at least one false positive grows with the number of tests. Adjusting significance and confidence levels aims to keep the overall chance of a Type I error at the chosen level (often 5%) across all analyses. A common method is to lower the alpha used for each test (for example, Bonferroni divides the overall alpha by the number of tests) and adjust the corresponding confidence intervals accordingly. This preserves the overall error rate, even though it may reduce the power of individual tests. The main goal, then, is to prevent spurious findings across multiple analyses, not to meet submission rules, increase power, or simply make interpretation easier.