Lecture

Calculations of Expectation

Description

This lecture covers the calculation of expectation and variance for different types of random variables, including discrete and continuous ones. It explains how to compute the expectation and variance using probability density functions and provides examples with T(k, X) and N(μ, σ²) distributions. The lecture also introduces the Cauchy distribution, a special case without expectation, and discusses the support, range, and invertibility of cumulative density functions.

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.

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.