Central Limit Theorem

This lecture covers the Central Limit Theorem, which states that the sum of a large number of independent and identically distributed random variables approaches a normal distribution. The instructor explains the convergence in law, characteristic functions, and the moment problem. The lecture also delves into tightness, inversion theorems, and the Fourier transform. Proofs and applications of the theorems are discussed, emphasizing the analytical properties of characteristic functions.