A mathematical statistics lecture isn't just about crunching numbers; it’s about learning the formal framework for uncertainty. It provides the rigor necessary for fields ranging from econometrics to machine learning. By mastering these theoretical foundations, you gain the ability to not just perform analysis, but to critique and create the statistical methods of the future.
Are all terms (e.g., "convergence in probability" vs. "almost surely") used precisely? mathematical statistics lecture
An estimator $\hat\theta$ is unbiased for $\theta$ if: $$E[\hat\theta] = \theta$$ The expected value of the estimator equals the true parameter. A mathematical statistics lecture isn't just about crunching