What Is Confidence Interval?
A statistical range that estimates where the true effect of an intervention likely falls, typically expressed as a 95% CI — meaning there's a 95% probability the true value lies within that range.
Why It Matters for Supplement Brands
Confidence intervals tell you more than p-values alone. A narrow CI around a meaningful effect size indicates a robust finding, while a wide CI that crosses zero suggests the result may not be reliable. When building substantiation files, studies with tight, positive CIs provide the strongest evidence.
How It Works
A 95% confidence interval is calculated from the study data and tells you: if this study were repeated 100 times, the true effect would fall within this range in 95 of them.
For example: 'Supplementation reduced cortisol by 12% (95% CI: 8%–16%)' means the true reduction is likely between 8% and 16%.
Key interpretation rules: - If the CI does not cross zero (for difference measures) or 1.0 (for ratio measures), the result is statistically significant - Narrower CIs indicate more precise estimates (usually from larger studies) - Two studies can have the same p-value but very different CIs — always check both
Common Mistakes to Avoid
- ✗Ignoring CI width and focusing only on whether the result is 'significant'
- ✗Confusing confidence intervals with prediction intervals (which are wider and serve a different purpose)
- ✗Not checking whether the CI crosses the null value before citing a study as evidence
Related Terms
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