Interval Estimation Task
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See: Estimation Task, Interval Estimate, Point Estimation Task, Confidence Interval.
References
2011
- http://en.wikipedia.org/wiki/Interval_estimation
- In statistics, 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. Neyman (1937) identified interval estimation ("estimation by interval") as distinct from point estimation ("estimation by unique estimate"). In doing so, he recognised that then-recent work quoting results in the form of an estimate plus-or-minus a standard deviation indicated that interval estimation was actually the problem statisticians really had in mind.
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
- In statistics, 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. Neyman (1937) identified interval estimation ("estimation by interval") as distinct from point estimation ("estimation by unique estimate"). In doing so, he recognised that then-recent work quoting results in the form of an estimate plus-or-minus a standard deviation indicated that interval estimation was actually the problem statisticians really had in mind.
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