Lecture

Random Vectors & Distribution Functions

Description

This lecture covers random vectors, joint distribution, transformed mass functions, conditional density functions, independence, and conditional independence. It also discusses marginal mass and density functions, covariance, correlation, and conditional expectation. The instructor explains the properties of multivariate random variables, moment generating functions, and the relationship between covariance and independence. The lecture concludes with a discussion on distribution functions and some housekeeping information regarding coursework deadlines.

Instructors (2)

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Official source

https://mediaspace.epfl.ch/media/0_2gim63kh

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Ontological neighbourhood

Statistics

Statistical inference: Mathematical statistics

Mathematics

Probability theory: Topics in probability theory

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