The gambler’s fallacy is an error in thinking about random events that arises from incorrect assumptions regarding previous results of such events. When thinking about them based on these previous results, people erroneously believe an event will occur more or less likely.
Predicting the gender of a child by counting how many boys or girls were born from one couple is one example of such analysis, while it also plays a part in trading and investing activities.
Misconception 1: The probability of different events is independent
Humans have the ability to discern patterns in our environment. Unfortunately, this ability can sometimes mislead us. One such misperception of probability is the gambler’s fallacy – the belief that an increasing number of events of one type makes it more likely that those events will repeat themselves again – an error which often causes people to make bad decisions in various settings.
Example: Observing that many have won the lottery may lead one to believe their next ticket could be successful; similarly, investors often liquidate stocks after experiencing numerous positive trading sessions in hopes that past gains will translate to future gains.
Teachers must recognize and assist their students in breaking free of gambling-style thinking so that they do not make incorrect calculations and conclusions during STEM studies. This will prevent their mistakes from extending into incorrect calculations or conclusions that hinder progress.
Misconception 2: The probability of different events is correlated
People frequently believe that an event’s probability increases or decreases according to previous outcomes, which is known as the gambler’s fallacy and one of the most prevalent irrational beliefs regarding probabilities.
The Gambler’s Fallacy is a type of representativeness heuristic that leads people to inaccurately predict random events. STEM teachers can help their students recognize this bias by emphasizing that one event does not determine or change future ones.
Psychotherapist Steven Pinker discusses apophenia – or the tendency to perceive meaningful connections between unrelated things – in this video. He provides examples such as Gambler’s Fallacy as evidence for this type of apophenia.
Gambler’s fallacy can lead to costly mistakes when investing in stocks or betting on sporting events. Early instruction of your STEM learners will ensure they make decisions based on empirical probability rather than relying on guesswork for outcome determination.
Misconception 3: The probability of different events is influenced by external factors
The gambler’s fallacy is an incorrect form of thinking in which people assume that external influences influence the probability of events such as coin flips. For instance, if all 10 coin flips have resulted in heads, many may conclude that future coin flips are less likely to also end in heads; this line of reasoning is incorrect as random events happen independently and past outcomes do not impact future outcomes.
An easier way of understanding cognitive distortions like the gambler’s fallacy is to remember that human judgment operates in two distinct modes when dealing with uncertainty: intuitive and analytical thinking. Gambler’s fallacy stems from system 2 thinking, commonly known as “system 2 thinking.”
Numerous correlational studies have demonstrated an association between Gambler’s Fallacy (GF) and problem gambling (PG), but only few behavioral studies have investigated it directly. This quasi-experiment examined its occurrence among both problem and non-problem gamblers using an imaginary roulette game as its method.
Misconception 4: The probability of different events is influenced by past events
Gamblers might assume that their next dice roll will produce sixes because there have been fewer sixes than anticipated in previous rolls; although this is an error in logic, this misconception can be overcome through understanding conditional probability.
An effective way of combatting the gambler’s fallacy is through understanding human cognitive biases that hinder predictions in various scenarios. An example is representativeness heuristic, which causes people to rely on short sequences of events to predict probability for future ones.
The gambler’s fallacy is particularly prevalent when flipping coins. Long runs of heads or tails aren’t uncommon and this often leads to people thinking the probability of getting one after several consecutive tosses of tails is greater than it actually is; however, this is not true as each coin toss stands on its own and does not increase after repeated tails tosses.