 That is, we assume that our data follow some unknown distribution formula_4 (where "θ" is a fixed constant that is part of this distribution, but is unknown), and then we construct some estimator formula_2 that maps observed data to values that we hope are close to "θ".The bias of formula_2 relative to formula_7 is defined as

where formula_9 denotes expected value over the distribution formula_4, i.e.averaging over all possible observations formula_3.