Texas sharpshooter fallacy

The Texas sharpshooter fallacy is an informal fallacy which is committed when differences in data are ignored, but similarities are stressed. From this reasoning a false conclusion is inferred.^[1] This fallacy is the philosophical/rhetorical application of the multiple comparisons problem (in statistics) and apophenia (in cognitive psychology). It is related to the clustering illusion, which refers to the tendency in human cognition to interpret patterns where none actually exist.

The name comes from a joke about a Texan who fires some shots at the side of a barn, then paints a target centered on the biggest cluster of hits and claims to be a sharpshooter.^[2][3]

Structure

The Texas sharpshooter fallacy often arises when a person has a large amount of data at their disposal, but only focuses on a small subset of that data. Some factor other than the one attributed may give all the elements in that subset some kind of common property (or pair of common properties, when arguing for correlation). If the person attempts to account for the likelihood of finding some subset in the large data with some common property by a factor other than its actual cause, then that person is likely committing a Texas Sharpshooter fallacy.

The fallacy is characterized by a lack of specific hypothesis prior to the gathering of data, or the formulation of a hypothesis only after data has already been gathered and examined.^[4] Thus, it typically does not apply if one had an ex ante, or prior, expectation of the particular relationship in question before examining the data. For example one might, prior to examining the information, have in mind a specific physical mechanism implying the particular relationship. One could then use the information to give support or cast doubt on the presence of that mechanism. Alternatively, if additional information can be generated using the same process as the original information, one can use the original information to construct a hypothesis, and then test the hypothesis on the new data. See hypothesis testing. What one cannot do is use the same information to construct and test the same hypothesis (see hypotheses suggested by the data) — to do so would be to commit the Texas sharpshooter fallacy.

Examples

• A Swedish study in 1992 tried to determine whether or not power lines caused some kind of poor health effects. The researchers surveyed everyone living within 300 meters of high-voltage power lines over a 25-year period and looked for statistically significant increases in rates of over 800 ailments. The study found that the incidence of childhood leukemia was four times higher among those that lived closest to the power lines, and it spurred calls to action by the Swedish government. The problem with the conclusion, however, was that the number of potential ailments, i.e. over 800, was so large that it created a high probability that at least one ailment would exhibit the appearance of a statistically significant difference by chance alone. Subsequent studies failed to show any links between power lines and childhood leukemia, neither in causation nor even in correlation.^[5]
• Attempts to find cryptograms in the works of William Shakespeare, which tended to report results only for those passages of Shakespeare for which the proposed decoding algorithm produced an intelligible result. This could be explained as an example of the fallacy because passages which do not match the algorithm have not been accounted for.
• Attempts to find cryptograms in the Bible.
• This fallacy is often found in modern-day interpretations of the quatrains of Nostradamus. Nostradamus' quatrains are often liberally translated from the original (archaic) French, stripped of their historical context, and then applied to support the conclusion that Nostradamus predicted a given modern-day event, after the event actually occurred. The Nostradamus quatrains that supposedly predicted 9/11 were not even original to Nostradamus, but were either cobbled together from parts of separate quatrains or created from whole cloth.^[6]

See also

• Anthropic principle
• Availability heuristic
• Confirmation bias
• Final cause
• Hoyle's fallacy
• Look-elsewhere effect
• Postdiction
• Ramsey theory
• Overfitting

Related fallacies

• Cum hoc ergo propter hoc
• Post hoc ergo propter hoc
• Correlative based fallacies
• Moving the goalpost, a related fallacy used to obtain the opposite conclusion.

References

External links

• Fallacy files entry