hrothgar, on 2020-August-01, 06:10, said:
Listen shiite for brains, I know that you're a short timer, don't know anyone on the forums, and seems to have some need to go and swing your dick around, so here's a bit of background information
I have multiple graduate degrees in this stuff including two from MIT.
(I graduated from there with almost a 5.0 average)
The job that I held before this one was the product manager for MATLAB's statistics system.
The job that I currently hold is Principle Data Scientist at Akamai
As for your "contributions" to this thread.
The Nyquist–Shannon sampling theorem comes out of signal processing. It describes the relationship between the frequency of a signal and the sample rate. It doesn't get used to determine the sample size for observational studies. It doesn't get used for classical power calculations.
> The robots were given random hands to play and random
> results were collected. They are not double-dummy.
> There is only one dummy in this conversation.
I agree.
It is the person who doesn't know that GIB uses double dummy solvers to determine its line of play
I'm really delighted to discover that Akamai has decided to employ a data scientist with principles.
KS is not the best test. Better is the G-test for independence. I simplified it for the Forum so that a comparison could be made with Chi-squared. Neither are necessary because the result is bleeding obvious.
It does not matter what underlying software process GIB uses. What GIB does do is simulate.
You have been told this multiple times on the forum. Please listen. I only had to be told once but I am a fast learner. It may use the DD to simulate, but that does not mean that the 'simulation' is correct.
You are only 'correct' until your opponent makes their next move. This is true for all equilibrium games. It is true in life as well. Everything is 'obvious' when you know what happened.
Recently several people on the Forum complained that the deals were biased on BBO.
Think about what they mean. Did they mean that they did not they they did not get enough Aces? enough Kings enough spades? Wake up. What did they mean?
To help people you need to step into their shoes to answer their question. What people are saying is: When I play against other people of roughly equal ability and I am sitting EWN or South I seem to lose more often.
These people are NOT asking a mathematical question they are asking something else entirely. They are getting bad scores and they are blaming it on the cards that they are being dealt or the seat they are sitting in or the weather or the Jews or something else equally nonsensical. This is the reason Trump got elected. Because people thought they could solve all their problems by magic.
What I have done here is to demonstrate empirically - that there is no ghost in the machine. Pit four robots against each other and it does not matter where they are seated EW is just as likely to come out on top as NS.
Being competent in one area does not ensure competence in every area.