Interval Estimate - short version

Provides a range of values that best describe the population.

Interval estimation is the use of sample data to calculate an interval of possible (or probable) values of an unknown population parameter, in contrast to point estimation, which is a single number.

The most prevalent forms of interval estimation are:

* confidence intervals (a frequentist method); and

* credible intervals (a Bayesian method).

Other common approaches to interval estimation, which are encompassed by statistical theory, are:

* Tolerance intervals

* Prediction intervals - used mainly in Regression Analysis

* Likelihood intervals

There is a third approach to statistical inference, namely fiducial inference, that also considers interval estimation. Non-statistical methods that can lead to interval estimates include fuzzy logic. An interval estimate is one type of outcome of a statistical analysis. Some other types of outcome are point estimates and decisions.

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