confidence interval

Confidence Interval

A range of values within which the true population parameter is estimated to fall with a stated probability — a 95% confidence interval means if you repeated the study 100 times, the true value would fall inside the interval about 95 times.

When you'd see it: Alongside any estimate drawn from a sample: conversion rate estimates, survey results, A/B test effect sizes. 'Our conversion rate is 4.2% (95% CI: 3.8%–4.6%)' means there's a plausible range around the point estimate.

Why it matters: Confidence intervals tell you not just the estimate but how precise it is. A narrow interval says you have good data; a wide interval says you have an unreliable estimate. A confidence interval that crosses zero means you can't rule out 'no effect' — which is different from a narrow interval that's entirely positive.

Common mistakes: Interpreting a 95% confidence interval as 'there's a 95% probability the true value is in this range.' The correct interpretation is about the repeated sampling procedure, not about the probability that any particular interval contains the truth.

Related P-value, statistical significance, T-test, hypothesis testing