Maximum Likelihood EstimationIntroduces maximum likelihood estimation for statistical parameter estimation, covering bias, variance, and mean squared error.
Detection & EstimationCovers the fundamentals of detection and estimation theory, focusing on mean-squared error and hypothesis testing.
Estimators and BiasExplores estimators, bias, and efficiency in statistics, emphasizing the trade-off between bias and variability.
Statistical EstimationExplores statistical estimation, comparing estimators based on mean and variance, and delving into mean squared error and Cramér-Rao bound.
