In statistics, interval estimation is the use of sample data to estimate an interval of possible values of a parameter of interest. This is in contrast to point estimation, which gives a single value.[1]
The most prevalent forms of interval estimation are confidence intervals (a frequentist method) and credible intervals (a Bayesian method).[2] Less common forms include likelihood intervals, fiducial intervals, tolerance intervals, and prediction intervals. For a non-statistical method, interval estimates can be deduced from fuzzy logic.