Interval estimation is a statistical technique used to estimate a range of values within which a population parameter, such as a mean or proportion, is likely to fall. Instead of providing a single value, it gives a lower and upper bound, offering a more comprehensive view of uncertainty in the estimate. This method often involves the use of confidence intervals, which indicate the level of certainty associated with the estimate. For example, a 95% confidence interval suggests that if the same sampling process were repeated multiple times, approximately 95% of the calculated intervals would contain the true population parameter.