This lecture covers the properties and definitions of conditional expectation, emphasizing the concept of measurability and integrability. The instructor demonstrates the relationships between random variables and the convergence monotone theorem, extending the definition of conditional expectation to positive variables. The lecture concludes with the importance of convex functions in defining conditional expectations.