Data Science and Statistics

Confidence Interval, explained

A confidence interval is a range that estimates an unknown quantity with uncertainty from sampling.

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Part of the Semantic Notion technical glossary.

Short Definition

A confidence interval is a range that estimates an unknown quantity with uncertainty from sampling.

Intuition

Instead of pretending a single estimate is exact, a confidence interval shows a plausible range based on the data.

Technical Definition

A confidence interval is constructed by a procedure that, under repeated sampling assumptions, contains the true parameter a specified proportion of the time.

Example

An A/B test may estimate a conversion lift of 2 percent with a 95 percent confidence interval from 0.5 to 3.5 percent.

Common Misunderstandings

A 95 percent confidence interval does not mean there is a 95 percent probability the fixed parameter is inside this one interval.

Confidence intervals depend on assumptions and sampling design.

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Essays that use this concept

Data Science and EvaluationConfidence Intervals Explained for Data Scientists

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