This lecture covers the concept of stopping times in stochastic processes, defining them as random variables and explaining their relation to filtrations. The optional stopping theorem is presented, showing the conditions under which certain information is possessed at a given time. The lecture also discusses F-measurable random variables and martingales, illustrating their properties and applications through examples and proofs.