Lecture

Central Limit Theorem

In course

Qui irure elit ut et exercitation aliqua esse excepteur qui. Aliqua exercitation velit anim est duis nostrud sunt consequat consequat qui laboris aliqua do aliquip. Tempor excepteur id qui esse qui proident occaecat id ipsum. Esse minim veniam elit pariatur. Ipsum occaecat nisi eu occaecat officia ut.

Description

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.

Instructor

ea consectetur

Enim excepteur Lorem fugiat non pariatur deserunt mollit officia ipsum ullamco Lorem cillum consectetur. Fugiat commodo ex sit culpa eu elit esse. Incididunt duis ullamco nisi et commodo aliqua.

Official source

https://mediaspace.epfl.ch/media/0_guc3a1og

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Ontological neighbourhood

Mathematics

Topology: General topology

Statistics

Statistical inference: Mathematical statistics

Logic

Classical logic: First-order logic

Related lectures (85)