Lecture

Modes of Convergence of Random Variables

In course

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Description

This lecture covers the modes of convergence of random variables, including Xm → x if tεdo, Xmªx if P A :) = `, Xm₂ ²³ X if FE[(xu, P(|Xu-x17E) 10, Xm ²³xx of Fxx (x Fx G) for all x where FxGx) is continuous. Implications and Lemmas are discussed to understand the convergence. The lecture also delves into the Central Limit Theorem and the Streng Law of Large Numbers, providing insights into approximations and probabilities involving sums of independent random variables.

Instructors (2)

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Official source

https://mediaspace.epfl.ch/media/0_icpasv44

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Ontological neighbourhood

Statistics

Statistical inference: Mathematical statistics, Statistical hypothesis testing

Mathematics

Probability theory: Topics in probability theory

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