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Bob Dancer Column - 18 MAY 2017

#1

Bob Dancer Column - 18 MAY 2017

The Important Message

http://www.gamblingwithanedge.com/the-important-message

or

<a href="http://www.gamblingwithanedge.com/the-important-message">
http://www.gamblingwithanedge.com/the-important-message</a>

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#2

LOL, a better way to do “confirmation” is with Bayesian Probability. A shortcut way is to look for at least one “confirmation” in 5 cycles, that gives you a 2/3rd% error rate if you have the “cycle” correct. A “cycle” is how you handle probabilistic events, for example something that happens 1 in 3 on average has a “cycle” of 3.

#3

I don’t understand how
Bayes’ Theorem isn’t garbage in, garbage out.
How would it determine, say, the chance that a machine is gaffed? It
requires an initial estimate of that chance.

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On Tue, Apr 18, 2017 at 12:12 PM, nightoftheiguana2…@…com [vpFREE] <vpF…@…com> wrote:

LOL, a better way to do “confirmation” is with Bayesian Probability. A shortcut way is to look for at least one “confirmation” in 5 cycles, that gives you a 2/3rd% error rate if you have the “cycle” correct. A “cycle” is how you handle probabilistic events, for example something that happens 1 in 3 on average has a “cycle” of 3.

#4

Tom wrote: “I don’t understand how
Bayes’ Theorem isn’t garbage in, garbage out.
How would it determine, say, the chance that a machine is gaffed? It
requires an initial estimate of that chance.”

I don’t think you’re using that hammer the right way. What you want to do is make an initial assumption of what the royal cycle is, or another jackpot cycle, then you use actual results as feedback of your initial assumption.

I think another problem is that you’re thinking of “results” as pure noise, but they are not pure noise, that’s the key to Bayes.

#5

Maybe I don’t understand it, then.
Let’s say I assume the royal flush cycle is 40,000. After 4 million hands on a particular machine,
I’ve hit 20 royals. Without including an
initial estimate, what would Bayes’ Theorem say is the chance that the cycle is
more than 40,000?

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On Tue, Apr 18, 2017 at 3:01 PM, nightoftheiguana2…@…com [vpFREE] <vpF…@…com> wrote:

Tom wrote: “I don’t understand how
Bayes’ Theorem isn’t garbage in, garbage out.
How would it determine, say, the chance that a machine is gaffed? It
requires an initial estimate of that chance.”

I don’t think you’re using that hammer the right way. What you want to do is make an initial assumption of what the royal cycle is, or another jackpot cycle, then you use actual results as feedback of your initial assumption.

I think another problem is that you’re thinking of “results” as pure noise, but they are not pure noise, that’s the key to Bayes.

#6

Tom wrote: “Maybe I don’t understand it, then.
Let’s say I assume the royal flush cycle is 40,000. After 4 million hands on a particular machine,
I’ve hit 20 royals. Without including an
initial estimate, what would Bayes’ Theorem say is the chance that the cycle is
more than 40,000?”

That’s 100 cycles, the SD is sqrt(100) = 10, so down 80 would be -8SD. I don’t need Bayes Theorem to know I’ve likely got a problem. -8SD is of course possible, but highly unlikely. Really, in the real world, if you go down 5 cycles without a hit, you should be thinking of what your options are, it might be time to be looking elsewhere or consider going to gaming. 5 cycles without a hit is of course possible, and will happen the more you play, but it’s a signal, the yellow light is on. You should seriously consider whether or not to throw more dollars down that rat hole. You don’t want to get caught in another American Coin Slot Scandal. Stuff like that could bust out some big bankrolls. You’re naive if you think stuff like this doesn’t happen in today’s world. Remember what Bernie Sanders says, the system is rigged. Don’t get caught in a bear trap. Remember also, there’s a selective bias to gambling, you only hear from the lucky ones about how easy it is to make money, the losers quietly sink away, like old heroin junkies, never to be heard from again.

#7

noti, it sounds like you agree with me that Bayes’ Theorem can’t calculate the number. Theoretically, going 1 hand without a royal is some indication that the machine is gaffed in favor of giving too few royals.

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On Wed, Apr 19, 2017 at 1:10 PM, nightoftheiguana2…@…com [vpFREE] <vpF…@…com> wrote:

Tom wrote: “Maybe I don’t understand it, then.
Let’s say I assume the royal flush cycle is 40,000. After 4 million hands on a particular machine,
I’ve hit 20 royals. Without including an
initial estimate, what would Bayes’ Theorem say is the chance that the cycle is
more than 40,000?”

That’s 100 cycles, the SD is sqrt(100) = 10, so down 80 would be -8SD. I don’t need Bayes Theorem to know I’ve likely got a problem. -8SD is of course possible, but highly unlikely. Really, in the real world, if you go down 5 cycles without a hit, you should be thinking of what your options are, it might be time to be looking elsewhere or consider going to gaming. 5 cycles without a hit is of course possible, and will happen the more you play, but it’s a signal, the yellow light is on. You should seriously consider whether or not to throw more dollars down that rat hole. You don’t want to get caught in another American Coin Slot Scandal. Stuff like that could bust out some big bankrolls. You’re naive if you think stuff like this doesn’t happen in today’s world. Remember what Bernie Sanders says, the system is rigged. Don’t get caught in a bear trap. Remember also, there’s a selective bias to gambling, you only hear from the lucky ones about how easy it is to make money, the losers quietly sink away, like old heroin junkies, never to be heard from again.