Fundamentals of Statistics contains material of various lectures and courses of H. Lohninger on statistics, data analysis and here for more.

Biased Estimator

An biased estimator is one which delivers an estimate which is consistently different from the parameter to be estimated. In a more formal definition we can define that the expectation E of a biased estimator is not equal to the parameter of a population. In principle we can differentiate between two types of bias:

  • location bias, where E(t) = τ + a, or a
  • scale bias, where E(t) = b*τ.

Note that an unbiased statistic is not necessarily an accurate statistic. If the variance of a statistic is high it can still be unbiased.