Lecture
This lecture covers the concept of Maximum Likelihood Estimation (MLE) in detail, focusing on properties such as equi-variance, invariance, and consistency. It explains the process of estimating parameters using MLE and discusses the proof of the Rao-Blackwell Theorem. The lecture also delves into the Exponential Family of distributions and demonstrates the consistency of MLE in different scenarios. Various examples are provided to illustrate the application of MLE in different statistical contexts.