![]() Back to: Management & Organizational Behavior How does the Texas Sharpshooter Fallacy Work? In simpler terms, it is the human tendency to see or even look for patterns in outcomes that are completely random. The Texas Sharpshooter Fallacy, commonly known as a clustering illusion or the hot hand fallacy, refers to the human tendency to analyze outcomes consisting of clusters in a random sequence of events as non-random. Other Logical Fallacies What is the Texas Sharpshooter Fallacy? The texas sharpshooter fallacy archive#(Also in USA Today's fee-only web archive at usatoday.Update Table of Contents What is the Texas Sharpshooter Fallacy? How does the Texas Sharpshooter Fallacy Work? The Texas Sharpshooter Fallacy vs. Johnson, "Cancer clusters are difficult to nail down", USA Today, Arlington, Apr 13, 1999, reproduced at, accessed December 16, 2002. Robert Todd Carroll, "Texas-Sharpshooter Fallacy", Skeptic's Dictionary, 01/03/02,, accessed December 16, 2002. Paul Cox, Glossary of Mathematical Mistakes, "Shooting the Barn' Statistics",, accessed December 16, 2002. Don't pick a target after you've fired your gun. But more importantly, decide on your hypothesis (what you are testing for) before you perform a test. The solution is twofold: firstly, when you see a cluster in any data, study the entire data so you know the likelihood of clusters forming this will give a clue as to whether the results are random. But tracking down the environmental cause often proves fruitless, because there is often no environmental reason, Erin Brockovich notwithstanding. Inevitably such clusters will exist, by statistical principles (helped, of course, because people are not always distributed uniformly), and they look impressive when drawn on maps. The classic occasion when such faulty reasoning has been made is when dealing with cancer clusters, areas of the country where cancer appears to occur more often than the average. The problem arises if a statistician then sees a region on a map where results appear to be clustered, draws a circle around them, and decides the increased occurrence must be non-random and hence significant. Similarly, if you toss a coin ten times you're likely to get two or three the same in a row, and highly unlikely to alternate head-tail-head-tail-head. In making statistical observations, results will not be distributed with total uniformity but will naturally be sparser in some areas and denser in others, purely by chance. The fallacy is due to a form of clustering illusion. The result: random impacts become highly significant. However, in an attempt to demonstrate his aim, our less skillful hero fires his gun into the side of a barn, then walks over and draws a target around area where most of his bullets hit. Most target shooters show their skill by attempting to shoot as close to a bullseye as possible. Otherwise known as " shooting the barn" statistics, or in German Zielscheibenillusion ("target illusion"), the analogy is with a marksman of dubious skills in the Lone Star State (no offence to Texans I believe his origin is irrelevant). In statistics, selective selection from results can prove almost anything. However, the question is whether such clusters are statistically meaningful. When you have a map showing a the occurrences of events the data set commonly seems to form clusters, regions with large numbers of data points. The Texas Sharpshooter Fallacy is a mistake statisticians can make when considering randomly- distributed data. ![]()
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