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As one book on the topic explains: Furthermore, the gambler’s fallacy can also influence people’s thinking and decision making in other areas of life beyond gambling. A similar phenomenon was described by French scholar Pierre-Simon Laplace, in the first published account of the gambler’s fallacy: As this shows, the issue underlying the gambler’s fallacy is the incorrect belief in local representativeness , which is people’s expectation that small samples (or small parts of large samples) will be representative of their parent population, since they expect the essential characteristics of the population to be represented not only globally in the entire population (or in large samples), but also locally in all its parts. This is also referred to as the law of small numbers , which is the incorrect belief that small samples are likely to be highly representative of the populations from which they are drawn, similarly to large samples. In addition, you can further internalize this concept by asking yourself or whomever you’re trying to help avoid this fallacy to explain how the dice might be able to influence the roll. This can be beneficial, since asking people to think through the process, instead of simply explaining it to them, can increase the likelihood that they will understand why this belief is false. Note : there are various statistical approaches, such as Bayesian inference , that can be used to assess the likelihood that supposedly independent events are not actually independent of one another. A distinction is sometimes drawn between two different types of the gambler’s fallacy: However, note that the outcomes of i.i.d. variables do not have to be equiprobable , which means that they do not need to have an equal probability of occurring. For example, even if a coin is unfair because it’s more likely to land on heads than tails, a series of tosses of this coin is still identically distributed, because the coin has the same probability of landing on heads each time. Debias Your Organization. Related Biases. The Gambler’s fallacy stems from our tendency to assume that if a random event has occurred many times in the past, that it will occur more or less often in the future.
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