Quant #20: Confidence Interval and Confidence Level

A confidence interval refers to the range of results that would be expected to contain the population parameter of interest. Confidence intervals reflect the degree of uncertainty (or certainty) in a sampling method. Typically, confidence intervals are built based on confidence levels (usually 90% or 95%).

The confidence level is the probability of obtaining the same results if a test or survey were to be repeated. Confidence level refers to the probability that the confidence interval would contain the true population parameter when you draw a random sample repeatedly. There are different levels but the most common confidence level is 95%. For example, a 95% confidence level indicates that the confidence interval would include the true value in 95% of all possible cases if the process were repeated under the same conditions.