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Psychological Phenomena

Texas Sharpshooter Fallacy

Probability and Statistical Reasoning Biases

The Texas sharpshooter fallacy is the statistical fallacy of inferring meaning from what is essentially a random distribution of data points, functioning as the philosophical or rhetorical application of the multiple comparisons problem, also known in statistics as data dredging or p-hacking, together with apophenia, a concept from cognitive psychology. It is related to the clustering illusion, the tendency in human cognition to interpret patterns where none actually exist, a tendency that itself stems from an underlying tendency to underestimate how likely clusters are to appear by chance in a random or pseudorandom dataset. The name comes from an anecdote about a person in Texas who fires a gun at random into the side of a barn, producing a random distribution of bullet holes, and only afterward paints a target around the tightest cluster of shots to claim to be a sharpshooter.

Facts
Core Claim
The Texas sharpshooter fallacy is the statistical fallacy of inferring meaning from what is essentially a random distribution of data points. 1
First Described Year
1977 1
Classification
Type of Phenomenon
Cognitive Phenomenon 1
Connections

In Branch

Source Texas sharpshooter fallacy, Wikipedia
Sources
1. Texas sharpshooter fallacy, Wikipedia
  • Lead section, first sentence
    The Texas sharpshooter fallacy is the statistical fallacy of inferring meaning from what is essentially a random distribution of data points.
  • Origin section
    In the modern statistical literature, the story of a specifically Texas sharpshooter is first mentioned in 1977.
  • lead section, phenomenon-kind classification
    It is the philosophical or rhetorical application of the multiple comparisons problem (also known as data dredging or p-hacking in statistics) and apophenia (in cognitive psychology).
  • In Branch: Cognitive Psychology, Categories
    Wikipedia article 'Texas sharpshooter fallacy' is filed under Category:Cognitive biases.
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