The Gauss-Markov theorem is a fundamental result in the theory of linear regression. It states that under some assumptions, the method of least squares gives unbiased estimates of the coefficients of the best-fit line with the minimum variance.
The Gauss-Markov theorem is a fundamental result in the theory of linear regression. It states that under some assumptions, the method of least squares gives unbiased estimates of the coefficients of the best-fit line with the minimum variance.