The representativeness heuristic is a concept in the social sciences that describes how people assume the likelihood of a particular outcome. A heuristic is a sort of mental shortcut or rule of thumb that can aid decisionmaking, but it can also lead to mistaken impressions about the world. Often, people don’t have accurate, complete access to general statistical information, such as the prior probability, or base rate, of certain things—like the likelihood of being in a car accident or becoming a millionaire. Instead, people rely on simplified ideas about the world. Studies with a sample size based on a small number of people often sway people’s decisionmaking.

The representative heuristic and the [availability heuristic](https://www.masterclass.com/articles/availability-heuristic-explained) are both heuristics that are often confused with one another. The representativeness heuristic has to do with superficial similarities between situations, leading to assumptions that appear accurate but are, in fact, false. The availability heuristic, on the other hand, is when an assumption is made based on recent information—usually because something like it has happened recently to the person making the assumption or because that thing looms large in the mind of the person.
Psychologists Amos Tversky and Daniel Kahneman first described the representativeness heuristic in the 1970s. The psychologists conducted a series of experiments and published their findings—many of which are compiled in the book *Judgment Under Uncertainty: Heuristics and Biases* (1974)—which were highly influential in the fields of cognitive psychology and behavioral science. Their work focuses on the psychology of prediction and subjective probability. 

In the classic study “Subjective probability: a judgment of representativeness” (Kahneman, D. and Tversky, A., 1972), the authors asked students to predict the major of a fictional grad student named Tom. The psychologists provided a brief description of the student, noting such characteristics as being highly intelligent, organized, somewhat self-centered, and socially awkward. Despite the low statistical likelihood of Tom being an engineering major, that’s what the majority of the students predicted.

In another experiment, the psychologists gave undergraduate students a description of a woman named Linda, then asked to predict the likelihood of her being a feminist, a bank teller, or both. Although the likelihood of her being both could not technically be higher than each description alone, the students did not take that aspect of probability into account, apparently misled by their heuristics about feminists and bank tellers.
A representativeness bias can occur for a few reasons, such as:

- __Mental prototypes__: People navigate the world with the help of normative models based upon their personal experience and what they’ve learned from trusted sources. These models don’t consider all the complexity of reality, leading to a flawed decisionmaking process.
- __Efficiency__: Most people don’t have the time to look up the statistical probabilities of different outcomes; instead, they often use mental shortcuts. This can also lead to errors in judgment, especially with quick decisions.
- __Resemblance__: People seem to be biased towards causes and effects resembling each other. Suppose they find themselves in a situation that appears to resemble previous ones they’ve heard about or have been in. In that case, they might conclude that the outcome previously experienced is more likely to occur than others, even if this isn’t statistically more likely than any other outcome.
The representativeness heuristic plays out quite frequently, and researchers attribute many <a href='https://masterclass.com/articles/how-to-identify-cognitive-bias' target='_blank' class='mc-text--link' data-mc-segment-trigger='true' data-mc-segment-event-type='Article Page Click' data-event-obj='{"textTag":"p","href":"https://masterclass.com/articles/how-to-identify-cognitive-bias","linkCopy":"cognitive biases","category":"automated-link"}' automatic='true'>cognitive biases</a> to this heuristic:

1. __Workplace__: Representativeness heuristic is especially common in the workplace and often leads to errors in management. Work situations that appear similar to past situations might have very different causes, leading to poor decisionmaking. The representativeness heuristic can also affect hiring decisions, specifically when racial bias or gender bias guide hiring choices.
2. __Medicine__: Doctors might make a diagnosis based on a particular patient’s resemblance to other patients with a similar set of symptoms or simply rely on a representativeness heuristic of the symptoms themselves, leading to poor outcomes. 
3. __Criminal justice__: In court cases, a jury might make a judgment based upon how well the accused matches their particular idea of a guilty person, rather than on a strict consideration of the available evidence.
4. __Discrimination__: People can quickly form stereotypes based upon simplistic readings of the world. When they act on these stereotypes, such as ideas regarding the profession, gender, race, and personality traits of another person, it can lead to bias and discrimination. Being aware of the representativeness heuristic can help people avoid this tendency.
These three fallacies are distinct, but researchers often trace them to the representativeness heuristic.

1. __Conjunction fallacy__: The conjunction fallacy is when an outcome is assumed to be caused by a conjunction of two specific conditions rather than a single, general one. Mathematically, the likelihood of a single person being two different things—like a military member and a hunter—is lower than those alone. Still, when people have a choice, they will assume that the conjunction is more likely, due to biases they have about different types of people.
2. __Gambler’s fallacy__: The gambler’s fallacy is the erroneous belief that, because an outcome has happened less frequently in the past, it is more likely to occur in the future. The classic example is a gambling scenario in which a dice roll or a coin toss frequency is predicted because a relatively long period has elapsed since that outcome last occurred. For example, suppose a seven hasn’t been rolled for many turns. In that case, a person might mistakenly assume it’s likely to happen very soon, even though the outcome of every roll is statistically independent of the past rolls.
3. __Regression fallacy__: This occurs when a result is assumed to be the effect of specific actions, rather than natural fluctuations. Suppose a person or group resolves an abnormal situation. In that case, they attribute the resolution to their activity when it could be simply a natural change. Suppose a person sees a doctor for a mysterious pain, and afterward, the pain subsides. In that case, it’s easy to attribute that result to the doctor’s intervention when it could be the natural ebbing of pain.
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Learn about the representativeness heuristic, a concept in the social sciences that affects decisionmaking.

Learn about the representativeness heuristic, a concept in the social sciences that affects decisionmaking.

How the Representativeness Heuristic Affects Decisionmaking

The representativeness heuristic is a concept in the social sciences that describes how people assume the likelihood of a particular outcome. A heuristic is a sort of mental shortcut or rule of thumb that can aid decisionmaking, but it can also lead to mistaken impressions about the world. Often, people don’t have accurate, complete access to general statistical information, such as the prior probability, or base rate, of certain things—like the likelihood of being in a car accident or becoming a millionaire. Instead, people rely on simplified ideas about the world. Studies with a sample size based on a small number of people often sway people’s decisionmaking.

What Is the Representativeness Heuristic? 

The representative heuristic and the <a href='https://www.masterclass.com/articles/availability-heuristic-explained' target='_self' class='mc-text--link' data-mc-segment-trigger='true' data-mc-segment-event-type='Article Page Click' data-event-obj='{"textTag":"p","href":"https://www.masterclass.com/articles/availability-heuristic-explained","linkCopy":"availability heuristic","category":null}'>availability heuristic</a> are both heuristics that are often confused with one another. The representativeness heuristic has to do with superficial similarities between situations, leading to assumptions that appear accurate but are, in fact, false. The availability heuristic, on the other hand, is when an assumption is made based on recent information—usually because something like it has happened recently to the person making the assumption or because that thing looms large in the mind of the person.

Representativeness Heuristic vs. Availability Heuristic 

Psychologists Amos Tversky and Daniel Kahneman first described the representativeness heuristic in the 1970s. The psychologists conducted a series of experiments and published their findings—many of which are compiled in the book Judgment Under Uncertainty: Heuristics and Biases (1974)—which were highly influential in the fields of cognitive psychology and behavioral science. Their work focuses on the psychology of prediction and subjective probability. In the classic study “Subjective probability: a judgment of representativeness” (Kahneman, D. and Tversky, A., 1972), the authors asked students to predict the major of a fictional grad student named Tom. The psychologists provided a brief description of the student, noting such characteristics as being highly intelligent, organized, somewhat self-centered, and socially awkward. Despite the low statistical likelihood of Tom being an engineering major, that’s what the majority of the students predicted.In another experiment, the psychologists gave undergraduate students a description of a woman named Linda, then asked to predict the likelihood of her being a feminist, a bank teller, or both. Although the likelihood of her being both could not technically be higher than each description alone, the students did not take that aspect of probability into account, apparently misled by their heuristics about feminists and bank tellers.

History of the Representativeness Heuristic 

A representativeness bias can occur for a few reasons, such as:<ul class="mc-m-4 list-styled"><li class="">Mental prototypes: People navigate the world with the help of normative models based upon their personal experience and what they’ve learned from trusted sources. These models don’t consider all the complexity of reality, leading to a flawed decisionmaking process. </li><li class="">Efficiency: Most people don’t have the time to look up the statistical probabilities of different outcomes; instead, they often use mental shortcuts. This can also lead to errors in judgment, especially with quick decisions. </li><li class="">Resemblance: People seem to be biased towards causes and effects resembling each other. Suppose they find themselves in a situation that appears to resemble previous ones they’ve heard about or have been in. In that case, they might conclude that the outcome previously experienced is more likely to occur than others, even if this isn’t statistically more likely than any other outcome. </li></ul>

Why Does the Representativeness Heuristic Bias Occur?

The representativeness heuristic plays out quite frequently, and researchers attribute many <a href='https://masterclass.com/articles/how-to-identify-cognitive-bias' target='_blank' class='mc-text--link' data-mc-segment-trigger='true' data-mc-segment-event-type='Article Page Click' data-event-obj='{"textTag":"p","href":"https://masterclass.com/articles/how-to-identify-cognitive-bias","linkCopy":"cognitive biases","category":"automated-link"}' automatic='true'>cognitive biases</a> to this heuristic:<ol class="mc-m-4"><li class="mc-my-4"> 1. Workplace: Representativeness heuristic is especially common in the workplace and often leads to errors in management. Work situations that appear similar to past situations might have very different causes, leading to poor decisionmaking. The representativeness heuristic can also affect hiring decisions, specifically when racial bias or gender bias guide hiring choices. </li><li class="mc-my-4"> 2. Medicine: Doctors might make a diagnosis based on a particular patient’s resemblance to other patients with a similar set of symptoms or simply rely on a representativeness heuristic of the symptoms themselves, leading to poor outcomes. </li><li class="mc-my-4"> 3. Criminal justice: In court cases, a jury might make a judgment based upon how well the accused matches their particular idea of a guilty person, rather than on a strict consideration of the available evidence. </li><li class="mc-my-4"> 4. Discrimination: People can quickly form stereotypes based upon simplistic readings of the world. When they act on these stereotypes, such as ideas regarding the profession, gender, race, and personality traits of another person, it can lead to bias and discrimination. Being aware of the representativeness heuristic can help people avoid this tendency. </li></ol>

4 Examples of the Representativeness Heuristic 

These three fallacies are distinct, but researchers often trace them to the representativeness heuristic.<ol class="mc-m-4"><li class="mc-my-4"> 1. Conjunction fallacy: The conjunction fallacy is when an outcome is assumed to be caused by a conjunction of two specific conditions rather than a single, general one. Mathematically, the likelihood of a single person being two different things—like a military member and a hunter—is lower than those alone. Still, when people have a choice, they will assume that the conjunction is more likely, due to biases they have about different types of people. </li><li class="mc-my-4"> 2. Gambler’s fallacy: The gambler’s fallacy is the erroneous belief that, because an outcome has happened less frequently in the past, it is more likely to occur in the future. The classic example is a gambling scenario in which a dice roll or a coin toss frequency is predicted because a relatively long period has elapsed since that outcome last occurred. For example, suppose a seven hasn’t been rolled for many turns. In that case, a person might mistakenly assume it’s likely to happen very soon, even though the outcome of every roll is statistically independent of the past rolls. </li><li class="mc-my-4"> 3. Regression fallacy: This occurs when a result is assumed to be the effect of specific actions, rather than natural fluctuations. Suppose a person or group resolves an abnormal situation. In that case, they attribute the resolution to their activity when it could be simply a natural change. Suppose a person sees a doctor for a mysterious pain, and afterward, the pain subsides. In that case, it’s easy to attribute that result to the doctor’s intervention when it could be the natural ebbing of pain. </li></ol>

3 Fallacies That Stem From the Represenativeness Heuristic

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Learn about the representativeness heuristic, a concept in the social sciences that affects decisionmaking.

Learn about the representativeness heuristic, a concept in the social sciences that affects decisionmaking.
