If 1 of these 100 confidence intervals is selected, we cannot say that there is a 95% chance it contains the true value of the parameter – this is a common misconception. Specifically, the confidence level indicates the proportion of confidence intervals, that when constructed given the chosen confidence level over an infinite number of independent trials, will contain the true value of the parameter.įor example, if 100 confidence intervals are computed at a 95% confidence level, it is expected that 95 of these 100 confidence intervals will contain the true value of the given parameter it does not say anything about individual confidence intervals. This confidence level, such as a 95% confidence level, indicates the reliability of the estimation procedure it is not the degree of certainty that the computed confidence interval contains the true value of the parameter being studied. If the parameter is the population mean, the confidence interval is an estimate of possible values of the population mean.Ī confidence interval is determined through use of observed (sample) data and is calculated at a selected confidence level (chosen prior to the computation of the confidence interval). A confidence interval is a statistical measure used to indicate the range of estimates within which an unknown statistical parameter is likely to fall.
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