Confidence Intervals

A confidence interval expresses the range within which a true value likely falls, given the uncertainty in your measurement. A 95% confidence interval means that if you repeated the same measurement process many times, 95% of the resulting intervals would contain the true value. The model's value for decision-makers is that it replaces false precision with honest ranges. A single number — "our conversion rate is 3.2%" — hides uncertainty. A confidence interval — "our conversion rate is between 2.8% and 3.6% with 95% confidence" — makes the uncertainty visible and forces you to ask whether the range is tight enough to act on.

When making data-driven decisions, demand confidence intervals rather than point estimates. Ask: how wide is the range? Is it narrow enough to distinguish between meaningful alternatives? If the intervals for two options overlap substantially, you don't have enough data to choose between them. Use this to decide when you need more data and when you have enough — the interval width tells you the cost of acting now versus waiting.

A confidence interval replaces false precision with honest uncertainty, showing the range within which the true value likely falls. Decisions based on point estimates without intervals are guesses in disguise.