An unbiased estimator of a population parameter is an estimator whose expected value is equal to the population parameter to be estimated.

Yes, that is correct! An unbiased estimator is a statistical estimator that, on average, hits the true parameter value across many samples. In other words, if you were to take an infinite number of samples from a population and compute the estimator each time, the average of those estimates would equal the actual parameter value you are trying to estimate.

For example, if you are estimating the mean $\mu$ of a population, an unbiased estimator for $\mu$ would be the sample mean $\bar{x}$. Its expected value is given by:

$E(\bar{x}) = \mu$

This reflects the property of being unbiased. If you have any specific questions or need further clarification on estimators, feel free to ask!