Gamblers fallacy

gamblers fallacy

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Gamblers fallacy -

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Gamblers' fallacy Definition: the fallacy that in a series of chance events the probability of one event occurring | Bedeutung, Aussprache, Übersetzungen und. Behavioral Finance: Der Gambler's Fallacy Effekt. April at |. Wenn Menschen Finanzentscheidungen treffen, tun sie das nicht immer rationell. Gamblers' fallacy Definition: the fallacy that in a series of chance events the probability of one event occurring | Bedeutung, Aussprache, Übersetzungen und.{/PREVIEW}

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This concept can apply to investing. They do so because they erroneously believe that because of the string of successive gains, the position is now much more likely to decline.

For example, consider a series of 10 coin flips that have all landed with the "heads" side up. Under the Gambler's Fallacy, a person might predict that the next coin flip is more likely to land with the "tails" side up.

Each coin flip is an independent event, which means that any and all previous flips have no bearing on future flips.

If before any coins were flipped a gambler were offered a chance to bet that 11 coin flips would result in 11 heads, the wise choice would be to turn it down because the probability of 11 coin flips resulting in 11 heads is extremely low.

The fallacy comes in believing that with 10 heads having already occurred, the 11th is now less likely. Something of this nature would surely have been reported in the press at the time, yet I have searched several online newspaper archives without finding any references to the event.

I removed a link to the inverse gambler's fallacy. The article with that title describes it as drawing the conclusion that there must have been many trials from observing an unlikely outcome.

The rather different concept this article was referring to was the belief that a long run of heads means that the next roll is outcome is likely to be heads.

Here are some sources that I'm considering for this page, and what they will contribute to the page:. Randomness and inductions from streaks: These researchers found that people are more likely to continue a streak when they are told that a non-random process is generating the results.

The more likely it is that a process is non-random, the more likely people are to continue the streaks. Useful explanation of the types of processes that are more likely to induce gambler's fallacy.

The gambler's fallacy and the hot hand: Empirical data from casinos. The Journal of Risk and Uncertainty 30, This is an observational study rather than an experiment, observing the behaviors of individuals in casinos.

I found it interesting that they also observed the "hot hand" phenomenon in gamblers as well - and that it's not just restricted to basketball.

The retrospective gambler's fallacy: Unlikely events, constructing the past, and multiple universes. Judgment and Decision Making, 4, This article introduces the retrospective gambler's fallacy seemingly rare event comes from a longer streak than a seemingly common event and ties it to real-world implications.

The researchers tie it to the "belief in a just world" and perhaps even hindsight bias the article talks about how memory is reconstructive.

The cognitive psychology of lottery gambling: Journal of Gambling Studies, 14, Ties the gambler's fallacy in with the representativeness and availability heuristic.

Defines gambler's fallacy as the belief that chance is self-correcting and fair. A gestalt approach to understanding the gambler's fallacy.

Canadian Journal of Experimental Psychology, 57 , Explains that simply telling people about the nature of randomness will not eliminate the gambler's fallacy.

Instead, the grouping of events determines whether or not gambler's fallacy occurs. Very interesting, and possibly a good source for a possible "solutions" section.

Biases in casino betting: The hot hand and the gambler's fallacy. Judgment and Decision Making, 1, Correlates hot hand and gambler's fallacy - people who exhibit one will also exhibit the other.

Introduces the possibility of a construct underlying both of these. One idea I had for possibly altering the structure of this article: If any of you would like to see some of the edits I'm planning for this page, you can check out my sandbox here.

This article was correctly assessed as a start. Huge tracts of it are not cited. The sources violate WP: It is clear the nominator was not familiar with or concerned with criteria at time of nomination and subsequently has not been interested because no work towards those criteria.

Demonstrated they are not interested in meeting criteria but meeting criteria. Suggest no one will bother to bring it up to GAN and I can't see this being done in a week.

It is entirely possible that the universe does have a 'memory' of events and that probability theory and the idea of randomness are not actually correct.

There is no way to prove probability theory. You can't prove probability theory by, for example, tossing a coin and counting results and comparing to expected results because you would actually have to use the theory to do that comparison.

The argument becomes circular. It is just one of the axioms we just accept in science. I work with probabilities and stats so I'm not saying it is wrong.

I'm pretty sure it is right and it's a great tool. But, I do find it fascinating that it may well be false and there is no way of knowing if it is or isn't.

There is, for example, no way to demonstrate or prove 'randomness'. We must simply state that a coin toss is random and accept it.

There are tests for randomness, but there are many sets of numbers that pass randomness tests that are in fact not random, the famous example being the Mandelbrot set.

These sets exist in nature frequently. It is only roughly true, with respect to large populations.

In human populations we see that there are slightly more male births than female ones, and it is believed that this difference is because more boy babies die before reaching reproductive age than girl babies.

This is called Fisher's Principle. The outcome for populations says nothing about the expected sex ratio of offspring of individuals.

Thus people who after having a series of children of the same sex who keep trying for the other, because they think in some sense 'they are owed one' are making the gamblers fallacy.

They may be strongly biased to produce the sex they already have produced, and the odds of them getting the other one may be very small. As of now we have no way to tell, because the mechanisms which determine the sex of offspring are largely unknown.

As far as I understand, this article is talking about the same concept as law of averages. Since the other article is shorter, would anyone be opposed to merging that article into this one?

I'm just now writing a response to someone who's brought up a difficult and fallacious argument. It's related to this topic, so I wanted to see if I could refer them here.

The problem is that the article is not written for the casual reader, but for the accomplished statistician. There needs to be extended text at the beginning that explains in simple and compelling language why this is a fallacy.

From the backtalk in the comments, there are a fair amount of people who are convinced they are still right. For example Carl from Louisiana, on Jan 15, Eebster the Great responded, but was more or less taking the correct and somewhat sterile party line.

I don't feel that's effective explaining to Carl and people like him why he's in error. We develop the belief that a series of previous events have a bearing on, and dictate the outcome of future events, even though these events are actually unrelated.

It is a cognitive bias with respect to the probability and belief of the occurrence of an event. Probability fallacies are of three types - 'near miss' fallacy, 'hot hand' fallacy, and 'gambler's' fallacy.

This causes him to wrongly believe that since he came so close to succeeding, he would most definitely succeed if he tried again.

Hot hand fallacy describes a situation where, if a person has been doing well or succeeding at something, he will continue succeeding.

Similarly, if he is failing at something, he will continue to do so. This presents a contrast to the gambler's fallacy , the definition of which is described below.

This fallacy is based on the law of averages, in the way that when a certain event occurs repeatedly, an imbalance of that event is produced, and this leads us to conclude logically that events of the opposite nature must soon occur in order to restore balance.

Such a fallacy is mostly observed in a casino setting, where people gamble based on their perception of chance, luck, and probability, and hence, it is called gambler's fallacy.

This implies that the probability of an outcome would be the same in a small and large sample, hence, any deviation from the probability will be promptly corrected within that sample size.

However, it is mathematically and logically impossible for a small sample to show the same characteristics of probability as a large sample size, and therefore, causes the generation of a fallacy.

But this leads us to assume that if the coin were flipped or tossed 10 times, it would obey the law of averages, and produce an equal ratio of heads and tails, almost as if the coin were sentient.

However, what is actually observed is that, there is an unequal ratio of heads and tails. Now, if one were to flip the same coin 4, or 40, times, the ratio of heads and tails would seem equal with minor deviations.

The more number of coin flips one does, the closer the ratio reaches to equality. Hence, in a large sample size, the coin shows a ratio of heads and tails in accordance to its actual probability.

This is because, despite the short-term repetition of the outcome, it does not influence future outcomes, and the probability of the outcome is independent of all the previous instances.

In other words, if the coin is flipped 5 times, and all 5 times it shows heads, then if one were to assume that the sixth toss would yield a tails, one would be guilty of a fallacy.

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Gamblers Fallacy Video

A Card Counter's Guide to the Gambler's Fallacy{/ITEM}

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fallacy gamblers -

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