Gonna do? He a mother-****in' hustler---you betta ask somebody!!

Hi, sorry for the simple question.

Playing 10-player sit 'n goes in a set of 3, all starting roughly at the same time, I figured that the average player (or a player who finishes in the money 30% of the time) will finish out of the money in all three games 34.3% of the time (.7^3) and therefore in the money in one or more games within the set 65.7% of the time. They will also finish all 3 games ITM 2.7% of the time. What is the percentage chance that they will cash in 1 of 3 and in 2 of 3 in the set?

I am a professor of mathematics. I expect to continue with this career.

Chaos theory says that we cannot predict the future because of sensitivity to initial conditions. Probability theory can say the same thing, but then we assign probabilities and we keep going with our analysis. So whether it is financial systems or something else, probability theory has more potential than chaos theory because it has all the same tools and then some.

Also, thank you for the opportunity to take advantage of #7 on the list of the Top 10 reasons to be a probabilist.

-grunch
Why do you call yourself a probabilist? What's the difference between you and me (mathematical statistician)?

Emphasis on teaching?

I'm partial to geometric and fractal brownian motion models.

Your welcome

In all probability it is better to post this question in the probability forum:

http://forumserver.twoplustwo.com/25/probability/


-Zeno

I hope that you did more than just estimate the probabilities in this otherwise excellent thread.

I doubt that "questions" even approximates a gaussian distribution, and it is somewhat questionable whether "forums" is nominal.

I have a question:
If you were to choose what kind of work you do in your career as probabilist what would it be ?
Would it be theoretical work on chosen area ?
Would it be some work on real life problems ?
Some mix of those ?
Something else ?

How does it relate to what you actually do ?

Can you really call yourself a mathematical statistician if you don't know the answer to this question?

A probabilist posts preprints here. A mathematical statistician posts preprints here. If you look at some of the posted preprints in those two locations, you can get a better understanding of the difference between the two fields.

According to the university, my official time allocation is 50% teaching, 47% research, and 3% service.

As a researcher in academics, I do in fact get to choose what I work on.

probably worth a bump

Since you work on LLNs and CLTs...I have a couple of questions.

Could you explain (intuitively if possible) the difference between MSE (mean squared error) convergence and convergence in probability? I guess all I need is a simple counterexample that shows the latter doesn't imply the former.


Another issue I'm having trouble with is how there can be something like an asymptotic variance if a r.v. converges in MSE on some value.

Finally, when it comes to estimation, wouldn't it be more worthwhile to identify consistent estimators that converge as rapidly as possible instead of those that are asymptomatically efficient? Is there a connection between the two, like do estimators that achieve the cramer rao lower bound converge more rapidly as well?

Suppose you make a monkey type on a typewriter for 10^18 seconds and the monkey can type 10 keys per second. There are 44 keys on the typewriter. Suppose Shakespeare's Hamlet is a sequence of 10^5 characters. What is the probability that the monkey will type at least one Hamlet.