In the previous module you learned that the Best Linear Unbiased estimator is Best because it yields the estimator with best precision. You may guess that precision is therefore an important measure for the quality of our estimation result. In this module we will look in more detail at the precision of our estimators and the interpretation.

Before doing so, we will use some examples to explain why it is important to assess the ‘quality’ of estimation.