The confidence level is designated before examining the data. In other words, 90% of confidence intervals computed at the 90% confidence level contain the parameter, 95% of confidence intervals computed at the 95% confidence level contain the parameter, 99% of confidence intervals computed at the 99% confidence level contain the parameter, etc. This means that the confidence level represents the theoretical long-run frequency (i.e., the proportion) of confidence intervals that contain the true value of the unknown population parameter. In general terms, a confidence interval for an unknown parameter is based on sampling the distribution of a corresponding estimator. For a given estimation in a given sample, using a higher confidence level generates a wider (i.e., less precise) confidence interval. The interval has an associated confidence level chosen by the investigator. This gives a range of values for an unknown parameter (for example, a population mean). In statistics, a confidence interval ( CI) is a type of estimate computed from the observed data. ( Learn how and when to remove this template message) ( March 2021) ( Learn how and when to remove this template message) ![]() ![]() Please help improve it to make it understandable to non-experts, without removing the technical details. This article may be too technical for most readers to understand.
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