Jul 28, 2020 13:02
I mean, the notation is getting "ugly", but yes it's valid. You can definitely fix points in the domain, condition on them, and take the expectation of the pdf you got by conditioning. In fact, you might want to pick an "easy" continuous distribution and see what you get if you take E(f(X)) (excluding all the conditioning stuff, which is only relevant as a process -- once you "un-condition" a conditional density (by "assuming" the condition), you have a "regular" density).
Jul 28, 2020 13:02
@nbro: I don't see the problem. The expected value operator is just an integral restricted to the sample space. The reality is that every real function from the sample space is a random variable. (Heck, there are "generalized" random variables, like random matrices, which are reified by mappings from the sample space to the space of matrices)
 
Feb 21, 2020 03:23
@Uueerdo: Canadian TV has "Continuum", which also has a "lot" (maybe a dozen characters) of people with time machines fighting a war in their own past. It was a good show.
 
Feb 6, 2020 12:59
He said he went and did it with management approval, since he is on downtime.
 
Jan 27, 2020 21:24
If you're still working on this, look up 18.3.1 at stat.rutgers.edu/home/hcrane/Teaching/582/lectures/…, which explains (well) what I was getting at (poorly).
Jan 27, 2020 18:28
You basically want to do an exact version of en.wikipedia.org/wiki/Simple_linear_regression (which is the statistical "sample" based argument)
Jan 27, 2020 18:27
By the way, I was slightly wrong -- Y isn't necessarily normal, BUT X and Y fit the axioms for the standard linear model, so the correlation is a...
Jan 27, 2020 18:27
I think the integral would be hard.
Jan 27, 2020 18:22
Because Y is a linear function of X, so Y is normal.
Jan 27, 2020 18:22
That depends. In this situation, (X,Y) are jointly normal, so there is a simple formula for the correlation and covariance. But if your book didn't cover it, you'll have to prove the formula.
Jan 27, 2020 18:22
do you have any formulas to calculate the covariance between X and Y? If so, look at the formula that defines C(X,Y) carefully and see what you can figure out based on the problem data.
Jan 27, 2020 18:22
Y is a linear function of X, so it is very much not independent. But there are formulas for this situation. (Not that I remember them at the moment, but perhaps they're in whatever book you're using).
 
Nov 3, 2019 19:25
Of course there is such a thing as "evidence of something not happening". It's "evidence that something else happened".
 
Jul 17, 2019 17:54
The epistemological foundations of mathematics are extremely murky, with the same approximate complexity and difficulty as "big" metaphysical topics as realism versus nominalism versus constructivism.
 
Apr 4, 2019 22:56
How is wealth "consumed", and how is that bad for society? 5 is an impossibility, and just bad rhetoric.
 

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Aug 24, 2014 03:42
so, that sounds good. thanks
Aug 24, 2014 03:42
we're all volunteers here, i gotcha :)
Aug 24, 2014 03:38
A lot of what I write about might be too focused on insurance for this blog. But maybe I can expand poissonlabs.com/blog/linearity-of-expectation into an article for next week.
Aug 24, 2014 03:32
and yes, the other blog is mine :)
Aug 24, 2014 03:32
i'm not sure. i write for that other blog first, and i think that if i think of appropriate topics for here, i'd be happy to expand and post
Aug 24, 2014 03:29
@mixedmath: i have a lot of experience with latex. :)
Aug 24, 2014 03:26
@mixedmath: just making sure you know, but I posted my draft for review.
Aug 24, 2014 02:08
I'm actually pretty used to Markdown + Mathjax. I just didn't know about $latex ...$
Aug 24, 2014 02:03
@AlexJBest: okay, thanks, I'll give that a try
Aug 24, 2014 01:31
Anyway, article submitted for review.
Aug 24, 2014 01:30
It doesn't seem like $x^2$ works. $$f(x) = ...$$ works fine for displaymode.
Aug 23, 2014 21:15
How does inline math mode word? dollar-foo-dollar doesn't seem to mathmode my foo's.
Aug 23, 2014 18:29
@mixedmath: Will Jagy, Binary Quadratic Forms
Aug 23, 2014 18:28
@mixedmath: yeah, what's up?
Aug 23, 2014 18:05
@mixedmath: super, thank you.
Aug 23, 2014 18:04
@mixedmath: okay, sounds good. I've signed in over there.
Aug 23, 2014 17:57
@mixedmath: I don't have anything ready yet, but I should be done in a couple of hours. After that, how does the submission process work? Where do I post or send it to?
Aug 23, 2014 17:39
Hello, I'm interested in writing an article on introductory actuarial science, aimed at an undergraduate audience. The goal of the article is to show how why insurance companies are better equipped to handle risk efficiently, and what it means for the risk that you and I, as customers, face. To that end, I would present a problem and work a problem on risk management.