This lecture introduces the concept of point estimators, which are used to estimate parameters of a statistical model. It covers the definition of parameters, different methods of estimation, such as the method of moments and maximum likelihood estimation, and provides examples to illustrate these concepts. The lecture also explains how to calculate estimators, variances, observed information, and Fisher information. Emphasis is placed on understanding the motivation behind estimation methods and how to choose between different estimators.