Confidence interval

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In statistics, a confidence interval (CI) is a tool for estimating a parameter, such as the mean of a population.^[1] To make a CI, an analyst first selects a confidence level, such as 95%. The analyst then follows a procedure that outputs an interval. By following this procedure many times across many experiments, the fraction of intervals that contain the parameter will approach the confidence level. It is a common misconception that the confidence level is the probability that a particular interval contains the parameter. Although these ideas are related, they are subtly different.

Factors affecting the width of the CI include the sample size, the variability in the sample, and the confidence level.^[2] All else being the same, a larger sample produces a narrower confidence interval, greater variability in the sample produces a wider confidence interval, and a higher confidence level produces a wider confidence interval.^[3]