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Confidence Interval ○꠹｜Definition｜1st｜20260715134324-00-⌔
Confidence interval - Wikipedia
Confidence interval
According to frequentist inference, a confidence interval (CI) is a range of values which is likely to contain (in repeated sampling) the true value of an unknown statistical parameter, such as a population mean.1 Rather than reporting a single point estimate (e.g. “the average screen time is 3 hours per day”), a confidence interval provides a range, such as 2 to 4 hours, along with a specified confidence level, typically 95%.
A 95% confidence level does not imply a 95% probability that the true parameter lies within a particular calculated interval, which is instead associated with the credible interval in Bayesian inference. The confidence level instead reflects the long-run reliability of the method used to generate the interval.23 In other words, if the same sampling procedure were repeated 100 times from the same population, approximately 95 of the resulting intervals would be expected to contain the true population mean. The frequentist approach sees the true population mean as a fixed unknown constant, while the confidence interval is calculated using data from a random sample. Because the sample is random, the interval endpoints are random variables.
Printed 2026-07-15.
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Link to original Footnotes
Hazra, Avijit (2017). “Using the confidence interval confidently”. Journal of Thoracic Disease. 9 (10): 4124–4129. doi:10.21037/jtd.2017.09.14. PMC 5723800. PMID 29268424. ↩
Dekking, Frederik Michel; Kraaikamp, Cornelis; Lopuhaä, Hendrik Paul; Meester, Ludolf Erwin (2005). “A Modern Introduction to Probability and Statistics”. Springer Texts in Statistics. doi:10.1007/1-84628-168-7. ISBN 978-1-85233-896-1. ISSN 1431-875X. ↩
“Confidence Intervals”. Yale Department of Statistics. Retrieved 2025-04-05. ↩
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