greeklandjohnny wrote:
>Here's a quickie outline of what the process should be:
>
>1) figure out what you want to prove. This can be due to previous play, rumors, second hand stories or whatever. Note that the previous play cannot be used to confirm or refute the hypothesis.
> You need to make this very specific
>
>2) Set up your experiment.
>
>3) decide on your acceptance criteria
>
>4) Post the info and let the stats guys go at it.
>
>For example, Miss Craps recently posted about going 0 for 35 on dealt trips on 10 play ( converting to quads). This is step 1. Miss Craps believes that the machines she was playing have a quad distibution outside the normal range. So, her hypothesis is that On machine xxx, the distribution of quads is much less can be expected.
>
>For step 2, you need to choose sample size and parameters. I will play 2000 dealt hands of triple play and record the number of times I am dealt trips and the number of times I convert them. I will also keep track of the total number of quads in the sample as an additional measure
>
>For step 3, I can pick 90% sure, 95% sure, 99% sure or whatever number I want. I will need to adjust the number of samples based on the frequency of the event and the confidence level
>
>Post the information and see what the group thinks.
>
>Is this a major pain? Sure it is. But is the only way to really know if there is an issue or not.
I don't see how this is adequate. What number are you trying to
determine? If the sample is x standard deviations from expected, what
chance of a gaffed machine does that translate to? A variable is
missing, but I'm not sure how to describe it. I've gone through the
kind of process you described and made conclusions based on it, but I
never ended up with a number which enabled me to say "I'm x% sure
what's being tested is gaffed." I still had to guess. At what point
is the probability that the machine is gaffed, say, 50%? Besides not
liking the idea of there being a significant possibility of going
years without winning even if the machines are fair, that I despair of
empirically proving they are fair is another reason I don't like
playing with a small theoretical advantage. Ultimately, it involves
trusting government.
