Seonglae ChoConfidence level
True value is expected to fall with a probability of Confidence level
Frequentist
When we calculate a confidence interval, this does not mean that there is a confidence level probability that the true parameter value lies within this specific interval. Instead, it means that if we were to repeatedly sample from the population and calculate confidence intervals in the same way, Confidence level probability of these intervals would be expected to contain the true parameter value.
Bayesian
Actually, the above description is incorrect. When we treat the parameter estimate as a random variable with a fixed sample interval, the probability that the true parameter lies within the interval equals the confidence level.
Confidence interval
In frequentist statistics, a confidence interval (CI) is a range of estimates for an unknown parameter. A confidence interval is computed at a designated confidence level; the 95% confidence level is most common, but other levels, such as 90% or 99%, are sometimes used. The confidence level represents the long-run proportion of CIs that theoretically contain the true value of the parameter. For example, out of all intervals computed at the 95% level, 95% of them should contain the parameter's true value.
https://en.wikipedia.org/wiki/Confidence_interval
