A confidence interval (CI) is one of the most widely abused and misunderstood ideas in statistical analysis. It is an attempt to provide an illustration of the uncertainty inherent in any estimate of a population value based on the value obtained from a random sample. This kind of illustration is intended to be used to help users and analysts to judge how good the estimate is. Unfortunately, the logic underlying the way in which CIs are used is flawed, in the same way as the logic of significance testing is, and anyway there is rarely a real-life situation where the assumptions necessary to calculate CIs are met. For those interested, this brief outline explains why. For everyone else, it is safe simply to ignore confidence intervals as irrelevant, overly complex, unrealistic and potentially misleading.
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