Lecture 7: Sigma Algebras
ฝัง
- เผยแพร่เมื่อ 19 ก.ย. 2024
- MIT 18.102 Introduction to Functional Analysis, Spring 2021
Instructor: Dr. Casey Rodriguez
View the complete course: ocw.mit.edu/co...
TH-cam Playlist: • Lecture 7: Sigma Algebras
Last time, we introduced outer measures, which have most properties we want for a measure. We define Lebesgue measurable sets and ultimately the Lebesgue measure. We also define sigma-algebras, including the important Borel sigma-algebra.
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Thanks
This mainly about definitions and the intricacies of proving what seems to be obvious but is not. Extremely fine attack.
Excelente, quem estuda análise bayesiana, é imprescindível aprender sigma-algebra
Plz upload complex analysis.
Alpha algebras are afraid of sigma algebras
Thank you.
Whats with the disclaimer at the start about this being recorded by a robotic camera? Has MIT of all places has run out of AV techs to record a lecture properly?
100:28 is it simpler to say E \in A => E^c \in A, so R = E u E^c \in A, so ø = R^c \in A ? (i.e. more direct from initial axioms)
Instead of the compactness argument at 21:00 why cant we consider (a + e/2 , b- e/2) is a subset of I so the lower bound on the outer measure of I is b-a - epsilon
I got the same confusion. For a finite interval, regardless of whether it is closed, open, or half-closed, it seems sufficient to prove that m^*(I) = \ell(I) by [a+e/2, b-e/2] \sub I \sub [a-e/2, b-e/2].
I thought this was some measure theory stuff :))) but some how it goes into functional analysis
This is pure measure theory, not functional analysis. I'm not sure why you are saying this "goes into functional analysis".
@@BigFish-ii8zdffs....Open the description slot....
Everything in maths is functional.
Exactly what is this used for? When would this be used in life?
This is building up for the Lebesgue integral which is used everywhere. Proability theory is a big application for instance.