Definition: Bias

Memobust Glossary

The bias of an estimator is the difference between its mathematical expectation and the true value of the parameter. In case it is zero, the estimator is said to be unbiased. Expectation is usually calculated on the set of all possible samples (Randomization approach). Otherwise is calculated with respect to the assumed model (model-based approach).

The bias of an estimator is the difference between its mathematical expectation and the true value it estimates. If this difference is zero, the estimator is said to be unbiased. Expectation is usually calculated on the set of all possible samples.

The bias of an estimator is the difference between its mathematical expectation and target parameter. In the case it is zero, the estimator is said to be unbiased. Expectation is usually calculated on the set of all possible samples.
Source:
Eurostat, ESSnet "Memobust", "Memobust Glossary" (part of the Memobust Handbook on Methodology of Modern Business Statistics), March 2014
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