Why is OLS Called an Unbiased Estimator?

The post explains why the OLS (Ordinary Least Squares) estimator in linear regression is considered an unbiased estimator. It details the concept of unbiasedness, showing that the expected value of the OLS parameter estimates, when computed over many samples, equals the true population parameter. An important takeaway is not to confuse unbiasedness with always obtaining the true parameter value from a single sample; rather, it means that the average estimate over multiple samples will equal the true parameter.