Understanding the role of the 95% confidence interval

Confidence intervals, particularly the 95% confidence interval, are a cornerstone of modern statistical analysis, offering a balance between avoiding false positives and maintaining a practical benchmark for research productivity. Established by Sir Ronald Fisher in 1925, the 95% confidence interval has remained a standard due to its defensibility, ubiquity, and practicality, filtering statistical noise and ensuring consistent communication across fields. While this threshold is often debated for its arbitrariness, its widespread acceptance provides a common language and framework for scientific inquiry. Adjustments to the confidence interval may be warranted based on specific risk profiles or statistical power considerations, such as in high-risk fields or when dealing with big data. However, any such modifications should be predetermined, consistently applied, and aligned with the unique requirements of the research context.