Lecture

Central Limit Theorem

In course

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Description

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.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_d6yg67vw

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Ontological neighbourhood

Mathematics

Analysis: Calculus

Topology: General topology

Probability theory: Topics in probability theory

Statistics

Statistical inference: Mathematical statistics

Information engineering

Signal processing: Fourier analysis

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