Logical Fallacy #23 - The Texas Sharpshooter

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]

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 a specific hypothesis prior to the gathering of data, or the formulation of a hypothesis only after data have 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 constructand test the same hypothesis (see hypotheses suggested by the data) — to do so would be to commit the Texas sharpshooter fallacy.