What Is Conjunction Fallacy? | Definition & Examples
The conjunction fallacy is the mistaken assumption that multiple events or conditions are more likely to occur together than they are to occur separately.
This reasoning demonstrates the conjunction fallacy because it incorrectly assumes that the likelihood of having both the flu and pneumonia is greater than the likelihood of having the flu alone. In reality, given that the patient has symptoms that are associated with both illnesses, it’s statistically more likely that a patient has the common flu, but not also pneumonia.
This error in reasoning can affect decision-making processes in contexts such as financial planning, medical diagnostics, and legal reasoning, among others.
What is conjunction fallacy?
The conjunction fallacy is the human tendency to mistakenly assume that multiple specific conditions are more probable than a single general condition (in this context, “conjunction” refers to the co-occurrence of multiple events or conditions).
In reality, the probability of any two events occurring together is always less than or equal to the probability of either event occurring independently. This principle is known as the conjunction rule in probability theory.
Despite its name, the conjunction fallacy is a cognitive bias (a pattern of irrational decision-making) rather than a logical fallacy. However, the same line of reasoning can also lead to flawed arguments.
The narrative fallacy is another cognitive bias that sometimes contributes to the conjunction fallacy. It reflects the human inclination towards coherent stories over statistical realities. This bias makes detailed narratives seem more credible than simple descriptions, despite statistical evidence to the contrary.
Conjunction fallacy examples
Examples of the conjunction fallacy can be seen in many domains, ranging from daily decision-making and professional judgments to academic research and policy development.
This example illustrates how the conjunction fallacy can sometimes be debunked by statistical data. The researcher made the mistake of assuming that two conditions (i.e., both protection against a disease and longevity) would be associated with a certain genotype. Yet, the statistical data contradicted this assumption, highlighting the importance of empirical evidence in debunking such misconceptions.
This cognitive bias affects how individuals assess the probability of combined events across fields such as psychology, finance, health, marketing, and beyond, leading to overestimations that can influence anything from personal choices to business strategies.
This scenario highlights the conjunction fallacy because the analyst overestimates the importance of multiple specific criteria over a single, more broadly relevant factor.
What is the psychology behind the conjunction fallacy?
The conjunction fallacy reflects a flaw in humans’ intuitive understanding of probability. This cognitive bias can be attributed to several psychological factors:
- Lack of knowledge of statistics: Statistical principles aren’t common knowledge, and most people aren’t familiar with concepts like the conjunction rule.
- Narrative bias: People are more likely to believe a detailed, coherent story than a more probable but less detailed scenario.
- Representativeness heuristic: People often judge the probability of an event or condition by how much it resembles a stereotype (e.g., many people would feel surprised if their new English literature professor comes in wearing jeans and sneakers, because it doesn’t match the stereotype).
- Confirmation bias: People tend to seek out and remember information that confirms their current beliefs, which can lead to overestimating the likelihood of conjunctions that fit with existing beliefs (e.g., assuming that a health-conscious individual is more likely to be a teacher and vegan rather than just a teacher).
What is the Linda problem?
The Linda problem is a well-known illustration of the conjunction fallacy. It demonstrates how people tend to make judgments based on heuristics (i.e., mental shortcuts) and subjective impressions rather than objective probabilities.
In a 1983 study by psychologists Amos Tversky and Daniel Kahneman, participants were presented with a description of Linda, a single 31-year-old woman who is passionate about social justice and anti-nuclear causes.
When asked to guess which description matched Linda, many participants incorrectly judged it more likely that Linda is both a bank teller and an active feminist rather than solely a bank teller.
The participants’ answer to this question defies the statistical principle that it’s more likely for conditions to occur separately than together. The Linda problem thus demonstrates the human tendency to commit the conjunction fallacy.
Frequently asked questions about conjunction fallacy
- Is the conjunction fallacy a heuristic?
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The conjunction fallacy is typically considered a type of heuristic or cognitive bias. These are mental shortcuts that people use to make judgments and decisions. The conjunction fallacy specifically refers to the tendency to incorrectly believe that the conjunction of two events is more likely than one of the events occurring alone.
- What is the conjunction rule in psychology?
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In psychology, the conjunction rule states that the likelihood of two events happening together cannot exceed the likelihood of either event happening independently.
This principle is fundamental to understanding logical reasoning and decision-making processes, particularly in contexts where individuals assess the likelihood of compound events.
The conjunction fallacy occurs when a person mistakenly believes the opposite: that two events are more likely to occur together than independently.
- When has someone committed the conjunction fallacy?
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The conjunction fallacy occurs when someone believes two events are more likely to occur together than separately. This error in judgment often arises in situations where individuals assess the likelihood of combined events without correctly applying the principle that the probability of joint occurrences cannot exceed the probability of individual occurrences.
