Estimation bias, or simply bias, is a concept in statistical inference that relates to the accuracy of parameter estimation. The term bias was first introduced in the statistical context by English statistician Sir Arthur L. Bowley in 1897. This entry provides the formal definition of estimation bias along with the concept of error, its implications and uses in statistical inference, and relevance to other types of bias that may arise in the data collection process.
Suppose that we would like to estimate a population parameter θ (e.g., population mean). An estimator is any sample statistic (e.g., sample mean) that is used to estimate θ. Because is sample based, it does not perfectly agree with the true value of θ. ...
Looks like you do not have access to this content.