Statistical confidence intervals are almost always misinterpreted. Consider the following statement. "The prevalence of the disease P has a 95% confidence interval of 1% <= P <= 5%." This is commonly taken to imply that there's a 95% chance that the true prevalence is between 1% and 5%. This isn't the case. Confidence intervals represent uncertainty about the interval, rather than … [Read more...]