LETTER TO THE BIG MAN, JOHN SOLITUDE..THE BIG MAN WRITES BACK

[TwoCatSam]

bj

As per Sam, I exaggerated:

BERLINER[4500€ better off thanks to the MAN called JOHN SOLITUDE]

Don't know where I got 6,000 Euro.

Sam

[Herb]

It's quite easy to prove the JS method doesn't work:

Prove: FACT, Roulette is a game of independent trials. 

JS (Clercx) has been gambling for only a couple of years. When he came up with his ideas, he failed to realize that roulette was a game of independent trials.  His poor understanding of roulette probability lead him to believe that events become due to catch up or hit when the standard deviation of the poorly performing numbers reach a certain standard deviation level.  Unfortunately, he also poorly understood how to use and interrupt the standard deviation testing. 

He wrote his JS methods in an attempt to make money.  His scam involved soliciting donations from people rather than charging out right for his system.  He also attempted to make money by trying to sell books via links form his chaotic and difficult to follow website. 




-----------------------------------------------
Here's more for you to read regarding the Gambler's Fallacy.

Gambler's fallacy
From Wikipedia, the free encyclopedia
Jump to: navigation, search
The gambler's fallacy, also known as the Monte Carlo fallacy or the fallacy of the maturity of chances, is the false belief that if deviations from expected behaviour are observed in repeated independent trials of some random process then these deviations are likely to be evened out by opposite deviations in the future. For example, if a fair coin is tossed repeatedly and tails comes up a larger number of times than is expected, a gambler may incorrectly believe that this means that heads is more likely in future tosses.[1] Such an event is often referred to as being "due". This is an informal fallacy.

The gambler's fallacy implicitly involves an assertion of negative correlation between trials of the random process and therefore involves a denial of the exchangeability of outcomes of the random process.

The inverse gambler's fallacy is the belief that an unlikely outcome of a random process (such as rolling double sixes on a pair of dice) implies that the process is likely to have occurred many times before reaching that outcome.

Contents [hide]
1 An example: coin-tossing
2 Psychology behind the fallacy
3 Other examples
4 Non-examples of the fallacy
5 References
6 See also
7 External links



[edit] An example: coin-tossing
The gambler's fallacy can be illustrated by considering the repeated toss of a coin. With a fair coin, the chances of getting heads are exactly 0.5 (one in two). The chances of it coming up heads twice in a row are 0.5×0.5=0.25 (one in four). The probability of three heads in a row is 0.5×0.5×0.5= 0.125 (one in eight) and so on.

Now suppose that we have just tossed four heads in a row. A believer in the gambler's fallacy might say, "If the next coin flipped were to come up heads, it would generate a run of five successive heads. The probability of a run of five successive heads is (1 / 2)5 = 1 / 32; therefore, the next coin flipped only has a 1 in 32 chance of coming up heads."

This is the fallacious step in the argument. If the coin is fair, then by definition the probability of tails must always be 0.5, never more or less, and the probability of heads must always be 0.5, never more or less. While a run of five heads is only 1 in 32 (0.03125), it is 1 in 32 before the coin is first tossed. After the first four tosses the results are no longer unknown, so they do not count. The probability of five consecutive heads is the same as that of four successive heads followed by one tails. Tails isn't more likely. In fact, the calculation of the 1 in 32 probability relied on the assumption that heads and tails are equally likely at every step. Each of the two possible outcomes has equal probability no matter how many times the coin has been flipped previously and no matter what the result. Reasoning that it is more likely that the next toss will be a tail than a head due to the past tosses is the fallacy. The fallacy is the idea that a run of luck in the past somehow influences the odds of a bet in the future. This kind of logic would only work if we had to guess all the tosses' results before they are carried out.

As an example, the popular doubling strategy of the Martingale betting system (where a gambler starts with a bet of $1, and doubles their stake after each loss, until they win) is flawed. Situations like these are investigated in the mathematical theory of random walks. This and similar strategies either trade many small wins for a few huge losses (as in this case) or vice versa. With an infinite amount of working capital, one would come out ahead using this strategy; as it stands, one is better off betting a constant amount if only because it makes it easier to estimate how much one stands to lose in an hour or day of play.


[edit] Psychology behind the fallacy
Amos Tversky and Daniel Kahneman proposed that the gambler's fallacy is a cognitive bias produced by a psychological heuristic called the representativeness heuristic [2][3]. According to this view, "after observing a long run of red on the roulette wheel, for example, most people erroneously believe that black will result in a more representative sequence than the occurrence of an additional red,"[4] so people expect that a short run of random outcomes should share properties of a longer run, specifically in that deviations from average should balance out. When people are asked to make up a random-looking sequence of coin tosses, they tend to make sequences where the proportion of heads to tails stays close to 0.5 in any short segment moreso than would be predicted by chance [5]; Kahneman and Tverksy interpret this to mean that people believe short sequences of random events should be representative of longer ones [6].

The representativeness heuristic is also cited behind the related phenomenon of the clustering illusion, according to which people see streaks of random events as being non-random when such streaks are actually much more likely to occur in small samples than people expect [7].


[edit] Other examples
The probability of flipping 21 heads in a row, with a fair coin is 1 in 2,097,152, but the probability of flipping a head after having already flipped 20 heads in a row is simply 0.5. This is an example of Bayes' theorem.

Some lottery players will choose the same numbers every time, or intentionally change their numbers, but both are equally likely to win any individual lottery draw. Copying the numbers that won the previous lottery draw gives an equal probability, although a rational gambler might attempt to predict other players' choices and then deliberately avoid these numbers (for fear of having to split the jackpot with them).

A joke told among mathematicians demonstrates the nature of the fallacy. When flying on an aircraft, a man decides always to bring a bomb with him. "The chances of an aircraft having a bomb on it are very small," he reasons, "and certainly the chances of having two are almost none!".

A similar example is in the film The World According to Garp when the hero Garp decides to buy a house a moment after a small plane crashes into it, reasoning that the chances of another plane hitting the house have just dropped to zero.

[berlinerbruce]

Hi Bruce, and All,


Regarding the 12-numbers sector hitting within 22 spins...

(Any 12-numbers set has the same probability as another to hit - a wheel-sector or a numerical dozen or a column or 12 randomly selected numbers doesn't matter; they are all 12 numbers - 12/37 to hit.)

Regards,
KFS

HI JFS, I looked up the JSWFA,,,, once again and that's where it conflicts, js says that lets say you've got 12 numbers and lets say 2 of them lay in a section, JS would tell us if the section has been hit say three times but not our 2 numbers JS would tell us that that our section has already hit 3 times so now our chances are of getting a hit on these two numbers are decreasing. He claims that after 100 spins sections on the wheel balance them self out o lot quicker than single numbers. Confused well I sure am,,,thanks for you help KFS by for now BERLINERBRUCE........WOW herb that was one hell of a statement you made there do you really think they are SCAMMERS

[Herb]

Simple luck.

[Herb]

Mr. Chips,

There is no disputing that roulette is a game of independent trials.  It's an absolute fact.  To argue otherwise is absurd.

[Herb]

*sigh*

For roulette not to be a game of independent trials, each pocket would have to be blocked from hitting again or a no spin would have to  be called if a number occurred more than once.

However, random roulette IS a game of independent trials.  A number is not blocked from hitting more than once.  Therefore the chance of a number hitting remains 1 in 37 or 1 in 38 at each spin, regardless of the numbers that occurred on the previous spins.

Arguing that roulette is not a game of independent trials is foolish.

[berlinerbruce]

OK OK HERB,     fact   is    it    THATS    WHAT     YOU    ARE    AFTER,,,,,,,,,,,,,,,   INDEPENDENT TRIAL     YOU     SAY,,,,,,berlinerbruce  SAYS  CORRECT   HERB,,,,,,,, THE WHEEL HAS NO MEMORY ALSO COORRECT,,,,,,,, 1 number has  INDEED ON EVERY SPIN THE SAME CHANCE OF APPEARING AS IT HAD FROM THE PREVIOUS,  but its a known fact that    A      GROUP OF NUMBERS lets say AFTER 50 -100 spins   will EVEN THEM SELFS OUT       BEFORE   12 INDUVIDAL NUMBERS WILL,,,,,,,,,,,,,,this     is       FACT....     NOT   LUCK HERB,,,,,,,siiiighhh.. I wait for the honarable member to reply,,,,BUT AS  ALWAYS KIND REGARDS BERLINERBRUCE

[Herb]

Let's discuss this in the chat.  I think you have a misunderstanding of roulette probability.

[Herb]

Mr. Chips,

You asked for proof, so I provided it.


Luck lasts as long as it lasts.  It ends when it ends.

[berlinerbruce]

HI MR C,  the reply your are receiving are quit NORMAL from a mathematician who can't explain a method or system that TRULY WINS and can stand the test of time IE   victors lw,,,for example    THE RAINDROP METHOD,,,,,,,,, by JOHN SOLITUDE, here are SOME OF THE MATHEMATICAL FORMULAS THAT OUR HERB USES TO DISCREDIT SUCH METHODS AND PEOPLE,,,,and I QUOTE,,,,,,,,,and boy boy AM I GONA QUOTE,,,,,,,,,garbage,,,,,,,,,luck,,,,,,,,simple luck,,,,,,,don't work,,,,,,hes just a scammer,,,,,,,,,,gamblers fallacy,,,,,,,,does need not to be tested,,,,,,,,,,,,,,,,   YOU OUT THERE     HERB,         YEEEEHAAAAAAAA,,,,,  CANT see much mathematical formulas there mr CHIPS CAN YOU,,,,,,,kind regards         berlinerbruce

[Herb]

Berlin,

I'm in the chat if you want to discuss this further.

[Kon-Fu-Sed]

Bruce,


You wrote "YOU OUT THERE     HERB,         YEEEEHAAAAAAAA,,,,,  CANT see much mathematical formulas there mr CHIPS CAN YOU,,,,,,,"

This was written by Herb:
"An example: coin-tossing
The gambler's fallacy can be illustrated by considering the repeated toss of a coin. With a fair coin, the chances of getting heads are exactly 0.5 (one in two). The chances of it coming up heads twice in a row are 0.5×0.5=0.25 (one in four). The probability of three heads in a row is 0.5×0.5×0.5= 0.125 (one in eight) and so on.

Now suppose that we have just tossed four heads in a row. A believer in the gambler's fallacy might say, "If the next coin flipped were to come up heads, it would generate a run of five successive heads. The probability of a run of five successive heads is (1 / 2) raised to the power of 5 = 1 / 32; therefore, the next coin flipped only has a 1 in 32 chance of coming up heads."


I have bold the formulas (it's actually only one) as you seemed to miss them. This is the only formula you will need.
But it's the basics, of course. You have to replace the numbers by what's relevant for you...

Example: The probability of three heads in three attempts is 0.5×0.5×0.5= 0.125... Says the text.
The same example for a selected 12 numbers (a 12/37 = 32.43% chance) to hit three times in three attempts: .3243 x .3243 x .3243 = .0341 = 3.41%
The exact answer is 1728 / 50653 which is calculated like this: (12 x 12 x 12) / (37 x 37 x 37) and gives 1/29.313 = 3.41% (quite close, anyway)

If you want to know the chance for a dozen to NOT hit at all (a 25/37 or 67.568% chance per attempt) in three attempts:
.67568 x .67568 x .67568 = .30847 = 30.847% OR
(25 x 25 x 25) / (37 x 37 x 37) = 15625 / 50653 = 1/3.242 = 30.847%

You can of course mix winning and losing % if you want to know, for example, the % for ONE EXACT "two wins and two losses in four attempts" (something like 4.8% for 12 numbers)

Simple as that.

BTW. The text talks about things happening "in a row".
That is, actually, not quite correct. It should be "in ... attempts".
There is nothing that says that you have to make your attempts in a row... As each and every number has the same probability to hit at each and every spin, independent trials, it doesn't matter which spins - as long as they are FUTURE ones, that is.


Happy multiplying!
KFS

PS. This is not an opinion of mine - it's a proven math formula.

[MattyMattz]

KFS, you explained that very well... nice job.

Matt

[Herb]

FYI,

What I wrote was a straight cut and paste from Wikapedia.

The text was also well written.

[berlinerbruce]

Hi lads, just like to thank you all for the feed back and its been read now over 790 times, as you can see its created a lot of interest. If you read my original post it wasn't to try to discredit the method nor credit it for anyone it was just to inform the player how the devils wheel has been behaving,regardless of what method a player wishes to play. A big thanks to you all for your advice and especially to MATTYMATZ ,HERB, got a guy calling round today to fix  that spreadsheet that MATTYMATZ kindly gave me, a great tool. Was playing at DB yesterday and 7 numbers of my section was on the third column the question is if the player was alerted to this would this alter the players decision,i think at least he would like to know, all the best BERLINER BRUCE.................I'm off its    SPITING   

[berlinerbruce]

-