bias

Bias

In statistics, the bias of an estimator $\hat{\theta }$ is the difference between the estimator’s expected value and the true value of the parameter being estimated:

$$\text{Bias}(\hat{\theta })=\mathbb{E}[\hat{\theta }]-\theta$$

An unbiased estimator converges to the true value as the dataset increases. That’s not neccessarily true for a biased estimator.