What does "Confidence Limit" mean?

Definition of Confidence Limit in the context of A/B testing (online controlled experiments).

What is a Confidence Limit?

Alias: confidence bound

A confidence limit is the lower or upper bound of a confidence interval (CI). It can be denoted by "LL" for lower limit and "UL" upper limit. A two-sided interval has two limits: one from below and one from above while a one-sided interval has just one limit: either a lower or upper one with the other being plus or minus infinity.

Since a confidence interval is constructed so that XX% of the time the true value of the parameter falls within the interval, the meaning of the limit once a particular interval is constructed is lost. One way to salvage it is to say, for example about a 95% one-sided interval with a lower bound, that if the true value is below the lower bound the interval would not have covered it with probability 95%. Another approach is to think about it in terms of a hypothesis test: any null hypothesis defined so that it falls entirely below the lower limit would be rejected at the 95% significance level or higher.

To take a more concrete example - if an observed lower interval limit of a 95% one-sided CI for relative difference in proportions (% lift) is at 3%, then we know that had the true lift been less than 3%, the experiment would have only produced such an outcome with probability less than or equal to 5%.

Like this glossary entry? For an in-depth and comprehensive reading on A/B testing stats, check out the book "Statistical Methods in Online A/B Testing" by the author of this glossary, Georgi Georgiev.

Related A/B Testing terms

Confidence IntervalConfidence Level

About the author

Georgi Z. Georgiev

Georgi has over twenty years of experience in online marketing, web analytics, statistics, and design of business experiments.

Author of the book "Statistical Methods in Online A/B Testing", white papers on statistical analysis of A/B tests, and a speaker, he has been distinguished as a winner in the Data & Analytics category of the 2024 Experimentation Thought Leadership Awards.

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