Clustering illusion

The illusion is caused by a human tendency to underpredict the amount of variability likely to appear in a small sample of random or pseudorandom data.

[1] Thomas Gilovich, an early author on the subject, argued that the effect occurs for different types of random dispersions.

Some might perceive patterns in stock market price fluctuations over time, or clusters in two-dimensional data such as the locations of impact of World War II V-1 flying bombs on maps of London.

[3][4][5][6][7] Using this cognitive bias in causal reasoning may result in the Texas sharpshooter fallacy, in which differences in data are ignored and similarities are overemphasized.

Daniel Kahneman and Amos Tversky explained this kind of misprediction as being caused by the representativeness heuristic[2] (which itself they also first proposed).