Why do we rely on specific information over statistics?

Base Rate Fallacy

, explained.
Bias

What is the Base Rate Fallacy?

When provided with both individuating information, which is specific to a certain person or event, and base rate information, which is objective, statistical information, we tend to assign greater value to the specific information and often ignore the base rate information altogether. This is referred to as the base rate fallacy or base rate neglect.

A colorful drawing illustrating the base rate fallacy. On the left, a stick figure named Steve says 'I am shy!' with a question asking if he is a salesperson or a librarian. In the middle, a person thinks 'Librarians are shy!' A bar graph on the right shows that there are more shy salespeople than shy librarians, indicating the correct answer is 'Salesperson.'

Where this bias occurs

If you’ve ever been a college student, you probably know that there are certain stereotypes attached to different majors. For example, students in engineering are often viewed as hardworking but cocky, students in business are stereotypically preppy and aloof, and arts students are activists with an edgy fashion sense. These stereotypes are wide generalizations, which are often way off the mark. Yet, they are frequently used to make projections about how individuals might act.

Renowned behavioral scientists Daniel Kahneman and Amos Tversky once conducted a study where participants were presented with a personality sketch of a fictional graduate student named Tom W. They were given a list of nine areas of graduate studies and told to rank them in order of likelihood that Tom W. was pursuing studies in that field. At the time, far more students were enrolled in education and the humanities than in computer science. However, 95% of participants said it was more likely that Tom W. was studying computer science than education or humanities. Their predictions were based purely on the personality sketch—the individuating information—with total disregard for the base rate information.1

As much as that one person in your history elective course might look and act like the stereotypical medical student, the odds that they are actually studying medicine are very low. There are typically only a hundred or so people in that program, compared to the thousands of students enrolled in other faculties like management or science. It is easy to make these kinds of snap judgments about people since specific information often overshadows base rate information.

Sources

  1. Kahneman D. and Tversky, A. (1973). On the Psychology of Prediction. Psychology Review. 80(4), 237-251. doi: 10.1037/h0034747
  2. See 1
  3. Chen, J. (2020). Base Rate Fallacy. Investopedia. https://www.investopedia.com/terms/b/base-rate-fallacy.asp
  4. Kahneman, Daniel; Amos Tversky (1985). "Evidential impact of base rates". In Daniel Kahneman, Paul Slovic & Amos Tversky (ed.). Judgment under uncertainty: Heuristics and biases. Cambridge University Press. pp. 153–160.
  5. Bar-Hillel, M. (1980). The base-rate fallacy in probability judgments. Acta Psychologica, 44(3), 211–233. doi: 10.1016/0001-6918(80)90046-3
  6. See 5
  7. See 1
  8. Kahneman, D., & Tversky, A. (1972). Subjective probability: a judgment of representativeness. Cognitive Psychology, 3(3), 430–454. doi: 10.1016/0010-0285(72)90016-3
  9. See1
  10. See 5
  11. See 5
  12. Epley, N., & Dunning, D. (2000). Feeling "holier than thou": are self-serving assessments produced by errors in self- or social prediction? Journal of Personality and Social Psychology, 79(6), 861–75. doi: 10.1037/0022-3514.79.6.861
  13. See 12

About the Authors

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Dan Pilat

Dan is a Co-Founder and Managing Director at The Decision Lab. He is a bestselling author of Intention - a book he wrote with Wiley on the mindful application of behavioral science in organizations. Dan has a background in organizational decision making, with a BComm in Decision & Information Systems from McGill University. He has worked on enterprise-level behavioral architecture at TD Securities and BMO Capital Markets, where he advised management on the implementation of systems processing billions of dollars per week. Driven by an appetite for the latest in technology, Dan created a course on business intelligence and lectured at McGill University, and has applied behavioral science to topics such as augmented and virtual reality.

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Dr. Sekoul Krastev

Sekoul is a Co-Founder and Managing Director at The Decision Lab. He is a bestselling author of Intention - a book he wrote with Wiley on the mindful application of behavioral science in organizations. A decision scientist with a PhD in Decision Neuroscience from McGill University, Sekoul's work has been featured in peer-reviewed journals and has been presented at conferences around the world. Sekoul previously advised management on innovation and engagement strategy at The Boston Consulting Group as well as on online media strategy at Google. He has a deep interest in the applications of behavioral science to new technology and has published on these topics in places such as the Huffington Post and Strategy & Business.

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