Ever wondered why Markov Chains in Monte Carlo methods converge after enough iterations?
Tanvir shared this link with me to find out why.
In Spring of 2010 I am taking two classes: MSCS 6020: Simulation (syllabus) and MSCS 6060: Parallel & Distributed Systems (syllabus).
In Fall of 2009 I took one class:
MSCS 6010: Probability which used Statistical Inference, Second edition by Casella & Berger.
Here is the syllabus for the course.
This past December, on the fifteenth, I completed the Probability class that I was attending.
We covered Probability from the theoretical (Calculus) and analytical (MATLAB) side of things. In my first foray into theory behind Statistics, I found the relationships between the distributions to be really neat to see, and along with the Calculus, a lot to chew on all at once ;).
Overall it was a lot of fun; I can’t wait to get started with Simulation on the eighteenth.
In the first half of the semester in the Probability course I am taking we learned (among other things) how to, given the probability distribution function for any distribution, derive, if possible, the:
Everyone seems to be excited about the second half of the semester when we will start building on this foundation.
The Powerball people seem like a cool bunch of people. Check this out.
Here is an article that explains how one of the four co-founders of SAS, a statistician, has an awesome job where the serious product (SAS) pays for him to develop the fun product (JMP).
Note: That is an understatement, as it probably would pay for him to stare at the ocean for the rest of his life if he wanted. It is still a good point, though: sell serious stuff to pay for the fun (for you) stuff.
The American Statistical Association, aka AMSTAT, is “[The United State’s] leading professional association for statistics.”.
Visit them here.
Check out this NY Times article discussing the demand for statisticians today.