Lecture
This lecture discusses the Central Limit Theorem (CLT) and its application to random variables. It covers the convergence of sums of independent and identically distributed random variables to a normal distribution. The theorem is proven using the concept of characteristic functions and moments. The lecture also explores the conditions under which the CLT holds and the implications of the theorem in statistical analysis.