The clustering illusion

The clustering illusion is a cognitive bias that occurs when individuals perceive patterns or clusters in random data, even when none exist. This bias can lead to the belief that certain events or outcomes are more likely than they actually are, and can result in individuals making decisions based on this false perception of patterns.

An example of the clustering illusion is a coin-tossing experiment in which individuals are asked to flip a coin a certain number of times and record the results. Some participants may notice that heads or tails seem to come up more frequently than the others, even though the coin is fair and the outcomes are truly random. They may conclude that the coin is not fair, even though the pattern that they perceive is simply a result of chance.

Another example of the clustering illusion is when individuals observe a sequence of stock market returns and perceive patterns, such as a series of up or down days, that are not actually there. They might conclude that the market is trending in a certain direction, even though the returns are truly random.

Paraphrased, the clustering illusion is a cognitive bias where individuals perceive patterns or clusters in random data, even when none exist. This bias can lead to the belief that certain events or outcomes are more likely than they actually are, and can result in individuals making decisions based on this false perception of patterns. An example of this might be in a coin-tossing experiment, where someone perceives a pattern of heads or tails coming up more frequently, even though the coin is fair, or in stock market returns, where someone perceives patterns that are not actually there and make decisions based on this false perception.