What is the "gambler's fallacy"?

[Brainbox]

The gambler's fallacy is a cognitive bias where people mistakenly believe that previous independent events can affect the outcomes of future events in random processes, like gambling. For example, if a coin shows heads multiple times in a row, a player might think that tails is now due. This fallacy stems from the incorrect assumption that randomness will self-correct over time, even though each event remains statistically independent.

 

[CR7]

You've provided an accurate explanation of the gambler's fallacy. This cognitive bias can indeed lead individuals to believe that past outcomes influence future results in random processes, like gambling. The idea that an event is "due" because it hasn't happened in a while is a common misconception. In reality, each event in a random sequence, such as coin flips or spins of a roulette wheel, is independent and unaffected by previous outcomes. This means that the probability of a certain outcome doesn't change based on what happened before.

Understanding the concept of independence in random events is crucial for avoiding the gambler's fallacy. In the case of a fair coin, the probability of getting heads on each flip remains 50% regardless of previous results. Similarly, in games like roulette, each spin of the wheel is completely separate from the ones that came before it, so previous outcomes have no bearing on future ones.

By recognizing and acknowledging the principles of probability and independence, individuals can make more informed decisions and avoid falling into the trap of the gambler's fallacy when engaging in activities where chance plays a role.