Bias (statistics)

Statistical bias is a feature of a statistical technique or of its results whereby the expected value of the results differs from the true underlying quantitative parameter being estimated. The bias of an estimator of a parameter should not be confused with its degree of precision as the degree of precision is a measure of the sampling error. Mathematically bias can be defined as:
Let formula_1 be a statistic used to estimate a parameter formula_2. If formula_3 then formula_4 is called the bias of the statistic formula_1, where formula_6 represents the expected value of the statistics formula_1. If formula_8, then formula_9. So, formula_1 is an unbiased estimator of the true parameter, say formula_2.
Types.
A statistic is biased if it is calculated in 
such a way that it is systematically different from the population parameter being estimated. The following lists some types of biases, which can overlap.