Lecture

Independence and Covariance

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In course

MATH-232: Probability and statistics (for IC)

Cours d'introduction à la théorie des probabilités et aux statistiques. ...

Description

This lecture covers the concepts of independence and covariance between random variables, exploring the conditions for independence and the implications of covariance. It delves into the calculation of conditional expectations, variance, and correlation, providing examples to illustrate these concepts. The lecture also discusses the mechanical computation involved in determining the covariance and the significance of independence in statistical analysis.

Instructors (2)

Raphaël Jean Berthier

Emmanuel Abbé

Teaching & PhD PhD Students Denys Pushkin, Ortal Yona Senouf, Vladyslav Shashkov Past EPFL PhD Students Elisabetta Cornacchia, Aryo Lotfi Courses Reasoning in artificial intelligence MATH-700 Large language models have raised the potential of artificial intelligence in various applications, including science and mathematics, but their reasoning capabilities remain under investigations. This class focuses on defining, measuring and improving the reasoning capabilities of such AI models. Awa

Official source

Ontological neighbourhood

Statistics

Statistical inference: Mathematical statistics

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