a note to you conspiracy theorists (or good news for stars)

[C M Burns]

ah good questions. To get this average probability, I computed the probability of a hand winning using twodimes.com, I believe their method is some sort of smulation, e.g. if it was AsQs vs. JcTc prob win = .X, then I averaged these to get the .66, maybe not the ideal way but it seemed reasonable. And you are right there could be some sort of sampling bias, I did try and not choose hands after the fact (e.g bad beats), but before the deal was complete. Of course all I show is that things turn out as they should, and how most would expect them too, so there is no reason to suspect a bias, even though you know how things should be it is just reasuring to play with some numbers and see they work out.

Now as for the person asking how 175 could be enough of a sample. Intuitvley it may not seem like enough, since 175 hands is nothing for gaging your results. Now if I were doing something like seeing if I got AA or KK the right amount of times or how often my set was drawn out on, 175, would be a ridiculously small and meaningless sample. But what I am doing is actually quite different. It would be more like having 175 times you had a set and seeing how often you are outdrawn. And even there how the hand was played would have much to do with the outcome. What I have is 175 hands where the expected outcome is totally dependent on chance (or the lay of the virtual cards). The next part should be more informative.

Essentially what I have is conceptually the same as trying to tell whether a coin is biased. There are some important difetrences like the probability of success is diferent for each trial, but the concept is the same. I have 175 event with a known probability of sucess, this would be like having 175 coin tosses, and you know the expected # of heads is .5.

So how then do you tell if a coin is biased. Well lets say you toss a coin 100 times, record the number of heads, then toss it 100 times again and record the number of heads, you continue to do this an infinate number of times. Now if you plot this "sampling distrobution" what you will get is a normal shaped curve. Most trials will have around 50 heads, but now with this distobution you can quantify how often a given number of heads will occur per trial. So what if you get 60 heads? As it turns out less than 2% of all of those sets of 100 tosses will have 60 or more heads, thus this is a fairly rare ocurence. So as someone said you can't prove anything with statistics but you can quantify its likleyhood. A comon criterion for "significance" or results unlikley to be caused by chance is 5%, meaning something that will ocurr by chance less than 5% of the time. So 60 heads out of 100 is suficiantly unlikley to happen by chance with a fiar coin that you should become suspicious of it's fairness.

Perhaps this does demonstrate somthing about intuitve probability. If I were to say to someone I got 60/100 heads they probably would not see this as all that unlikley, when actually you would get this result a very small % of the time by chance. So much so in fact that you would have to be a "sucker" not to at least be suspicious. For more info on probability and stats cunsult your school library.

Well thats todays lesson, tommorow we will discuss how a bill becomes law. Anyhow, I'm not saying my results are without flaw, it is just a little something that sugests things are as they should be, something to insight furry into those who claim a bias and also to show that I am a dork who like to play with numbers.

[GrannyMae]

One sane voice in a mob of torch-carring Phillistines.

i knew termite season had just started, and i knew you would sniff this thread out like a fallen redwood. however, what's with the philistine comment?
(other than your spelling error)

you are one piece of shiit mr. grand wizard

[JWise]

[ QUOTE ]
ah good questions. To get this average probability, I computed the probability of a hand winning using twodimes.com, I believe their method is some sort of smulation, e.g. if it was AsQs vs. JcTc prob win = .X, then I averaged these to get the .66, maybe not the ideal way but it seemed reasonable. And you are right there could be some sort of sampling bias, I did try and not choose hands after the fact (e.g bad beats), but before the deal was complete. Of course all I show is that things turn out as they should, and how most would expect them too, so there is no reason to suspect a bias, even though you know how things should be it is just reasuring to play with some numbers and see they work out.

Now as for the person asking how 175 could be enough of a sample. Intuitvley it may not seem like enough, since 175 hands is nothing for gaging your results. Now if I were doing something like seeing if I got AA or KK the right amount of times or how often my set was drawn out on, 175, would be a ridiculously small and meaningless sample. But what I am doing is actually quite different. It would be more like having 175 times you had a set and seeing how often you are outdrawn. And even there how the hand was played would have much to do with the outcome. What I have is 175 hands where the expected outcome is totally dependent on chance (or the lay of the virtual cards). The next part should be more informative.

Essentially what I have is conceptually the same as trying to tell whether a coin is biased. There are some important difetrences like the probability of success is diferent for each trial, but the concept is the same. I have 175 event with a known probability of sucess, this would be like having 175 coin tosses, and you know the expected # of heads is .5.

So how then do you tell if a coin is biased. Well lets say you toss a coin 100 times, record the number of heads, then toss it 100 times again and record the number of heads, you continue to do this an infinate number of times. Now if you plot this "sampling distrobution" what you will get is a normal shaped curve. Most trials will have around 50 heads, but now with this distobution you can quantify how often a given number of heads will occur per trial. So what if you get 60 heads? As it turns out less than 2% of all of those sets of 100 tosses will have 60 or more heads, thus this is a fairly rare ocurence. So as someone said you can't prove anything with statistics but you can quantify its likleyhood. A comon criterion for "significance" or results unlikley to be caused by chance is 5%, meaning something that will ocurr by chance less than 5% of the time. So 60 heads out of 100 is suficiantly unlikley to happen by chance with a fiar coin that you should become suspicious of it's fairness.

Perhaps this does demonstrate somthing about intuitve probability. If I were to say to someone I got 60/100 heads they probably would not see this as all that unlikley, when actually you would get this result a very small % of the time by chance. So much so in fact that you would have to be a "sucker" not to at least be suspicious. For more info on probability and stats cunsult your school library.

Well thats todays lesson, tommorow we will discuss how a bill becomes law. Anyhow, I'm not saying my results are without flaw, it is just a little something that sugests things are as they should be, something to insight furry into those who claim a bias and also to show that I am a dork who like to play with numbers.

[/ QUOTE ]

I never had a problem with your sample size my problem was you stated you were testing to see if the deal is bias towards fish

what if the favorite only won 40% of the time will you then be able to conclude the deal is bias towards the fish?

[Fred Duke]

I'm still just an Associate Wizard.

Don't let that torch go out in the wind.

[Fred Duke]

Looks like solid work. Two Dimes might enumerate all boards yielding the exact odds, not a simulation. Either way your .66 number won't be off by much.