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. More general forms of erroneous pattern recognition are pareidolia and apophenia. Related biases are the illusion of control which the clustering illusion could contribute to, and insensitivity to sample size in which people don't expect greater variation in smaller samples. A different cognitive bias involving misunderstanding of chance streams is the gambler's fallacy.
Daniel Kahneman and Amos Tversky explained this kind of misprediction as being caused by the representativeness heuristic9 (which itself they also first proposed).
Gilovich, Thomas (1991). How we know what isn't so: The fallibility of human reason in everyday life. New York: The Free Press. ISBN 978-0-02-911706-4. 978-0-02-911706-4 ↩
Kahneman, Daniel; Amos Tversky (1972). "Subjective probability: A judgment of representativeness". Cognitive Psychology. 3 (3): 430–454. doi:10.1016/0010-0285(72)90016-3. /wiki/Doi_(identifier) ↩
Clarke, R. D. (1946). "An application of the Poisson distribution". Journal of the Institute of Actuaries. 72 (3): 481. doi:10.1017/S0020268100035435. https://www.actuaries.org.uk/documents/application-poisson-distribution ↩
Gilovich, 1991 p. 19 ↩
Mori, Kentaro. "Seeing patterns". Retrieved 3 March 2012. http://forgetomori.com/2009/skepticism/seeing-patterns/ ↩
"Bombing London". Archived from the original on 2012-02-21. Retrieved 3 March 2012. https://web.archive.org/web/20120221221013/http://www.dur.ac.uk/stat.web/bomb.htm ↩
Tierney, John (3 October 2008). "See a pattern on Wall Street?" (October 3, 2008). TierneyLab. New York Times. Retrieved 3 March 2012. /wiki/John_Tierney_(journalist) ↩