Confidence Interval
A range of values that likely contains the true population parameter with a specified probability.
Also known as: CI, Margin of error, Uncertainty interval
Category: Concepts
Tags: statistics, uncertainties, measurement, research, analysis
Explanation
A confidence interval is a range of values that, given the data, likely contains the true value of what you're measuring. A 95% confidence interval means: if we repeated this study many times, 95% of the calculated intervals would contain the true value. Confidence intervals communicate: the point estimate (best guess), the uncertainty (width of interval), and the precision (narrower = more precise). Why they're better than p-values: they show magnitude and uncertainty together, they enable comparing effects visually, and they're more intuitive than binary significant/not-significant. Interpreting confidence intervals: if interval doesn't include zero, effect is 'significant' at that confidence level; narrow intervals indicate precise estimates; overlapping intervals suggest effects may not differ. What confidence intervals are NOT: they don't tell you the probability the true value is in this specific interval (that's either 0% or 100%); the probability refers to the procedure, not this particular interval. For knowledge workers, confidence intervals help: understand uncertainty in estimates, compare findings more meaningfully, and recognize that point estimates alone are incomplete without their uncertainty.
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