- [[properties of variance]] # Idea An estimator is unbiased if the expected value of the estimates it produces is equal to the true parameter of interest. $\hat{b}$ is an unbiased estimator if the expected value of $\hat{b}$, $E(\hat{b})$ is equals to $\beta$: $ E(\hat{b})=\beta $ # References - [The Mean and Variance of Estimated Regression Parameters in a Full Rank Gauss-Markov Linear Model - YouTube](https://www.youtube.com/watch?v=jyBtfhQsf44)