Live data from Hacker News

Introduction to Stochastic Processes [pdf]

web.ma.utexas.edu

11–13 of 13 posts

Re: Introduction to Stochastic Processes [pdf]

#11
post #5
post #4

Earlier quoted context omitted.

seconded, his grad probability classes were some of my favorites a few years ago (also hi!). Measure theoretic probability significantly influenced how I think about nearly everything today, which is as strong an endorsement of these notes as I can muster.

Just out of curiousity, can you say a bit about how it influences your every day thinking? And why is measure theory so essential to really understanding probability? I sort of understand why it's necessary to have the language of measure theory and be able to talk about the measures/probabilities of uncountable sets but don't really understand beyond that. I have the equivalent of an undergrads understanding of meas…

Intuitively for me probability theory is a bit clunky before measure theory. Like we have a different equation for expectations if something is continuous vs a discrete distribution. We use probability density functions (pdf) vs a probability mass function (pmf) and etc.

We know this stuff is basically getting at the same underlying quantities. Now imagine a distribution over both continuous and discrete. For example something that measures temperature but breaks after a certain threshold. What does the expectation be for such an instrument? Imagine a distribution on different sized arrays of real numbers. How do you define a valid density function? Measure theory gives you the formalisms for those kinds of problems. You in practice don't need it very often but it keeps you on firm ground when you do.

Re: Introduction to Stochastic Processes [pdf]

#12

Earlier quoted context omitted.

Prior to giving real analysis and measure theory a serious go, I feel as though I was carrying around quite a lot of notation baggage that was essentially opaque to me. A lot of it was simply "received knowledge" and not at all cleanly organized in my mind. For example, I remember fumbling over a modelling problem involving mixed random variables (that is, random variables with both continuous and discrete parts), an…

Do you think that real analysis and measure theory helped you get a better grip on the notion of a r.v. than just the simple function from sample space to real line definition? I'm slightly tempted to take or at least try to self-study real analysis and eventually measure theory, but everyone I know (including profs) has told me not to bother if I'm not going to do theoretical stuff.

It depends what you mean by "getting a better grip". There are books on scientific topics that do not rely on technical details. When they are great, they are so exactly because, even with this constraint, they manage to clearly convey the elemental notions to a layman ([0] is a great example). It is debatable whether the grip you get in this way is better or not. Certainly it can get deeper, when complemented with the right analytical tools.

[0] - https://www.amazon.co.uk/Relativity-Routledge-Classics-Bertr...

Post reply on HN