The clustering illusion is the tendency to mistakenly perceive patterns or clusters in random data. This cognitive bias arises because humans often underestimate the variability that can occur in small sample sizes of random distributions. As a result, people may see streaks or clusters that are simply products of chance.
An example of the clustering illusion can be seen in stock market price fluctuations, where investors mistakenly believe that a series of price increases or decreases indicates a trend, rather than recognizing it as a random occurrence.
To overcome the clustering illusion, it is important to consider larger sample sizes and analyze data statistically to understand the genuine patterns versus those that are mere fluctuations of randomness.