Estimator
In statistics, an estimator is a rule for calculating an estimate of a given amount based on observed data: thus the rule (the estimator), the amount that is being measured (the estimand) and its result (the estimate) are different.[1]
An estimator of a parameter [math]\displaystyle{ \theta }[/math] is often written as [math]\displaystyle{ \hat\theta }[/math].[2] If the expected value of the estimator is equal to the parameter, then the estimator is called unbiased. Otherwise, it is called biased.[3]
Estimator Media
A estimator curve the has high frequency accumulated at the center and low frequency on two sides
A bad estimator example
The comparsion between a good and a bad estimator
Related pages
References
- ↑ Mosteller, F.; Tukey, J. W. (1987) [1968]. "Data Analysis, including Statistics". The Collected Works of John W. Tukey: Philosophy and Principles of Data Analysis 1965–1986. Vol. 4. CRC Press. pp. 601–720 [p. 633]. ISBN 0-534-05101-4 – via Google Books.
- ↑ "List of Probability and Statistics Symbols". Math Vault. 2020-04-26. Retrieved 2020-09-12.
- ↑ Taylor, Courtney (January 13, 2019). "Unbiased and Biased Estimators". ThoughtCo. Retrieved 2020-09-12.
Other websites
- Fundamentals on Estimation Theory Archived 2020-02-12 at the Wayback Machine