I honest to God don't know why YT recommended me this video, as I'm not even a STEM person (maybe it's cuz I previously checked out some Machine Learning videos to see what the fuss was, I guess). But, I really liked your video! Amazingly I understood almost everything! Maybe it's cuz you initially framed this thing as a language, which is a really helpful headspace for us non-tech folks to get into when trying to understand stuff. Also, your motivating examples, like why we can substitute complements in the field conditions via De-Morgan's etc., really helped. This was so weird & fun. You've got a sub! 🤗
I haven't yet taken a course in measure-theoretic probability but my Bayesian statistics class just covered such concepts (as review) in its first week. I have been trying learning it from readings and class discussions. Your lecture, thanks to its engaging style and clear examples, has been a great source of learning.Thank you so much! Eagerly awaiting future lectures.
Fabulous !!! :D :D :D I loved your mathematical statistics course and am currently learning Markov chains from your videos. I've always struggled with measure theory for some reason (despite being "decent" at real analysis). But I really want to understand it to get better at some of my favorite math topics. I hope this course will change my perception about measure theory. Is there a course website which has the schedule of topics covered and the associated readings/textbooks/notes etc?
Great. I was taught probability theory as an applied scientist I.e. as fact, without proofs. In some fields like quant finance, every discussion starts with a statement about sigma algebras, Borel sets, filtrations and all sorts of gobbledygook which makes no sense to me. This may help…
@@AProbabilitySpace Hi, is it because AUB is not necessarily in the set? But I am confused. We are supposed to take the union from n =1 to infinity and show that (iii) is not fullfilled. How do we achieve that? Can we do AUBUAUBAUB... repeatedly?
I was lucky to take classes with Jem in person. She is simply awesome! The most genuinely effective teacher that every student should have.
Dan! Great to hear from you!
I honest to God don't know why YT recommended me this video, as I'm not even a STEM person (maybe it's cuz I previously checked out some Machine Learning videos to see what the fuss was, I guess). But, I really liked your video!
Amazingly I understood almost everything! Maybe it's cuz you initially framed this thing as a language, which is a really helpful headspace for us non-tech folks to get into when trying to understand stuff. Also, your motivating examples, like why we can substitute complements in the field conditions via De-Morgan's etc., really helped.
This was so weird & fun. You've got a sub! 🤗
Fabulous! Already the clearest intro on this topic out there. KEEP GOING!!
🎉finally. I have waited for so long. ❤❤
I haven't yet taken a course in measure-theoretic probability but my Bayesian statistics class just covered such concepts (as review) in its first week. I have been trying learning it from readings and class discussions. Your lecture, thanks to its engaging style and clear examples, has been a great source of learning.Thank you so much! Eagerly awaiting future lectures.
Thank you for your kind words, the next lecture is coming soon!
Вот это я понимаю! Спасибо за подробное и последовательное объяснение!
Thanks a lot for this course. I have hoping to find it for some time.
Thank you for the great lecture 🎊
I loved the space background!
Glad you enjoyed it!
What a great presentation.
Fabulous !!! :D :D :D I loved your mathematical statistics course and am currently learning Markov chains from your videos. I've always struggled with measure theory for some reason (despite being "decent" at real analysis). But I really want to understand it to get better at some of my favorite math topics. I hope this course will change my perception about measure theory. Is there a course website which has the schedule of topics covered and the associated readings/textbooks/notes etc?
What book recommendations do you have for this subject? Thank you for posting such amazing knowledge for the world to share and enjoy!
I recommend "First Look At Rigorous Probability Theory" by Rosenthal, and, if you want to go deeper, "Measure Theoretic Probability" by Billingsley. 🙂
You are an amazing teacher!
You are too kind. 🌼
Perhaps this is a naive question, but what prerequisites do you recommend for learning measure theoretic probability?
Real analysis would be the best but at least something proof based. :) Good luck!
Great. I was taught probability theory as an applied scientist I.e. as fact, without proofs. In some fields like quant finance, every discussion starts with a statement about sigma algebras, Borel sets, filtrations and all sorts of gobbledygook which makes no sense to me. This may help…
👍
9:47 I can't think of an example where (i) and (ii) is fulfilled but (iii) is not fulfilled.
How about the empty set, a set A, a set B, A complement, B complement, and Omega?
@@AProbabilitySpace Hi, is it because AUB is not necessarily in the set? But I am confused. We are supposed to take the union from n =1 to infinity and show that (iii) is not fullfilled. How do we achieve that? Can we do AUBUAUBAUB... repeatedly?
Would you recommend a book to follow along?
Hi. I'm not really following a book but I like Rosenthal's "A First Look at Rigorous Probability Theory"!
🐮👍
Why couldn't we define the final set in the video as (0, 1-e] for a small e instead of (0,1) in order to make it fit within F?
Can you share the notes?
I'm sorry, I don't really have any. :(
20000 in my pocket.