Anchoring Bias Heuristic & Decision Making: Definition and Examples

Take-home Messages

  • An anchoring bias is a faulty heuristic which occurs when you focus on one piece of information when making a decision or solving a problem. People make inaccurate final estimates due to inaccurate adjustments from an initial value.
  • Examples of the anchoring bias can be seen in a wide variety of everyday experiences, including medical diagnoses, relationships, and monetary decisions.
  • The anchoring bias can be influenced by a variety of factors, including mood, personality, and experience.
  • One can avoid the anchoring bias by educating oneself about the bias, being in a positive mood, being agreeable and open to experience, and being experienced in the given task (Englich & Soder, 2009; Caputo, 2014; Welsh et al., 2014).

Anchoring Bias Heuristic

Anchoring bias is closely related to the decision-making process, and occurs when we rely too heavily on either pre-existing information or the first piece of information (the anchor) when making a decision.

 Anchoring Bias Example

The idea of the anchoring bias originated in a 1974 paper by Amos Tversky and Daniel Kahneman called Judgment under Uncertainty: Heuristics and Biases (Tversky & Kahneman, 1974).

This paper introduced three major heuristics or biases that humans use in the processes of judgment and decision-making: the representativeness heuristic, the availability heuristic, and the adjustment and anchoring heuristic (Tversky & Kahneman, 1974).

Each of these heuristics plays a significant role in our everyday decision-making, usually without us even knowing.

Tversky & Kahneman illustrated the anchoring bias through an experiment where they asked participants to make estimations of an amount, such as “the percentage of African countries in the United Nations”.

After a wheel of fortune was spun to choose a random number, the participant was asked to determine if the chosen number was greater than or less than the amount that they would estimate afterwards (Tversky & Kahneman, 1974, p. 1128).

They found that the group that received an initial number of 10 had a lower median estimate (x = 25) than the median estimate for the group that received an initial number of 65 (x = 45) (Tversky & Kahneman, 1974).

Both group’s estimations were clearly influenced by their starting values. The groups both gave an uneven amount of weight to the initial value, causing their final estimates to be swayed in the direction of that initial value.

Tversky and Kahneman also demonstrated the anchoring bias in another experiment, in which one group was told to estimate the answer to 8 x 7 x 6 x 5 x 4 x 3 x 2 x 1, while another group was told to estimate the answer to 1 x 2 x 3 x 4 x 5 x 6 x 7 x 8 (Tversky & Kahneman, 1974).

Due to the properties of multiplication, these equations are equivalent, but Tversky and Kahneman found that the group who estimated the former equation had a median estimate of 2,250, while the group who estimated the latter equation had a median estimate of only 512 (Tversky & Kahneman, 1974).

These results confirmed Tversky and Kahneman’s predictions, which they explained using the idea that “people may perform a few steps of computation and estimate the product by extrapolation or adjustment” (Tversky & Kahneman, 1974, p. 1128).

In other words, people most likely multiplied the first few numbers in the sequence and then estimated their final answer based on that product.

The group who estimated the former equation would be estimating based on a product of about 336, while the group who estimated the latter equation would be estimating based on a product of about 6.

This leads to a large difference between the average estimates between the two groups, which emphasizes both the significance and the scale of the anchoring bias.

Why it Happens

One explanation of why the anchoring bias occurs is due to the primacy effect. The primacy effect is the tendency for people to remember things that they learn first better than things that they learn later on (Stewart et al., 2004).

This can help explain the anchoring bias because it explains why people cognitively assign greater importance to an initial value and do not assign adequate importance to subsequent information.

If people remember the initial value more than they remember the subsequent information, then they will be more likely to think that the initial value is more important than the subsequent information, often without even realizing this thought process.

Examples of the Anchoring Bias


An example of the anchoring bias can be found in the medical field, when a diagnosis is made based heavily on the initial symptoms that the patient experienced and less heavily on subsequent symptoms.

Doctors may depend too much on the initial information regarding the patient and not enough on additional information, which could be dangerous, as it may lead to a misdiagnosis.

An example of this can be seen with COVID-19 (Yousaf et al., 2020). A 2020 study raises the concern that doctors may fall prone to the anchoring bias when diagnosing patients with COVID-19, and therefore may fail to properly diagnose future issues that arise with these patients (Yousaf et al., 2020).

This highlights the potential damage that the anchoring bias can cause, as both misdiagnosis and missed diagnoses can put patients in real danger.


The anchoring bias can be applied to relationships. People may judge their relationships with someone based too much on the beginning of the relationships.

In terms of shorter-term relationships, this emphasizes the importance of first impressions. If you have a positive first impression on someone, they will most likely think positively of the relationship in general, whereas if you have a negative first impression on someone, they will most likely think negatively of the relationship in general.

This is due to them thinking largely about the first encounter or encounters that you all have had when thinking about the relationship overall.

For long-term relationships, this has significant consequences, as one may be more likely to stay in a toxic, unhealthy relationship, if the beginning of the relationship was healthy and positive.

This may explain why some people stay in relationships that are harmful to them, which is commonly quite difficult for other people to understand.


The anchoring bias can be seen in monetary judgments and decision-making. For example, how much we are willing to pay for a product can be influenced by this bias.

If the first time we encounter an item’s price, it is significantly lower than the next time(s) we encounter it, we would likely not be willing to pay more for it.

The opposite is true as well, as if the first time we encounter an item’s price, it is significantly higher than the next time(s) we encounter it, we would likely be very willing to pay for it.

Another example of how the anchoring bias can influence monetary decisions is within salary negotiations. If you are negotiating a salary and your boss begins with an initial salary that is low, after negotiating you might be more likely to accept a lower salary than you would have if your boss had begun with a higher initial salary.

This thinking may also be applied to a variety of other negotiation types.

These examples of the anchoring bias in monetary situations highlight the important role that this bias can play in economics.

Influencing Factors

The anchoring bias can be influenced by a variety of factors, including mood, personality, and experience. The effect of this bias can be either increased or decreased by different aspects of these factors.


Two experiments conducted by researchers Englich and Soder in 2009 found that mood can have an influence on the anchoring bias (Englich & Soder, 2009). More specifically, they found that the anchoring bias can be avoided by a positive mood (Englich & Soder, 2009).

This adds another item to the lengthy list of benefits that being in a positive mood has compared to being in a negative mood.

In addition, two studies conducted by Bodenhausen et al. in 2000 found that people who are sad are more likely to experience anchoring bias than people who are feeling neutrally (Bodenhausen et al., 2000).

A 2013 study confirmed this result, also finding that people in a sad mood are more prone to the anchoring bias (Chen, 2013). Interestingly, this study found that this difference was only found when the participants were not having to work hard cognitively (Chen, 2013).

This may suggest a role of cognitive workload within the anchoring bias.


Personality also has been found to influence the anchoring bias (Caputo, 2014). More specifically, being agreeable and being open to experience are two personality traits that can make people less prone to this bias (Caputo, 2014).

While personality traits are largely innate to a person, people can still strive to apply these traits to different situations in which they want to avoid the anchoring bias.

Being open to experience may make people less prone to this bias because it allows them to consider new information more thoughtfully and thoroughly, and they therefore may assign more weight than others to the new information and not rely so heavily on the initial information.


A third influencing factor of the anchoring bias is experience (Welsh et al., 2014). Researchers found that participants” performance level in a card game increased over time, which suggests that experience has an influence on the anchoring bias (Welsh et al., 2014). This shows that the more than someone participates in a certain activity, the less likely they are to experience the anchoring bias within that activity.

How to Avoid the Anchoring Bias

The anchoring bias can lead to incorrect judgments, so it is important to know how to avoid this bias. The first step to not falling prey to the bias, like many others, is educating oneself about the bias: what it is and why it happens.

When you are aware of the bias, it is easier to spot when you may be applying it and to then stop yourself from using it.

Circling back to research addressed above, the anchoring bias can also be avoided by being in a positive mood (Englich & Soder, 2009).

While it may be difficult to suddenly shift one’s mood in different circumstances, one can also use this information to become more aware of when they may be falling prey to the anchoring bias, as they would understand that they are more likely to experience this bias when they are in a sad mood.

Additionally, the anchoring bias may be avoided by being more experienced in a task (Welsh et al., 2014). One may therefore practice a task in order to avoid the anchoring bias in future experiences involving that task.


Bodenhausen, G. V., Gabriel, S., & Lineberger, M. (2000). Sadness and susceptibility to judgmental bias: The case of anchoring. Psychological Science, 11 (4), 320-323.

Caputo, A. (2014). Relevant information, personality traits and anchoring effect. International Journal of Management and Decision Making, 13 (1), 62-76.

Chen, Q. (2013). The Influence of Mood States on Anchoring Effects (Doctoral dissertation, The Ohio State University).

Englich, B., & Soder, K. (2009). Moody experts—How mood and expertise influence judgmental anchoring. Judgment and Decision making, 4 (1), 41.

Epley, N., & Gilovich, T. (2006). The anchoring-and-adjustment heuristic: Why the adjustments are insufficient. Psychological science, 17 (4), 311-318.

Stewart, D. D., Stewart, C. B., Tyson, C., Vinci, G., & Fioti, T. (2004). Serial Position Effects and the Picture-Superiority Effect in the Group Recall of Unshared Information. Group Dynamics: Theory, Research, and Practice, 8 (3), 166.

Tversky, A., & Kahneman, D. (1974). Judgment under Uncertainty: Heuristics and Biases. Science, 185 (4157), 1124–1131.

Welsh, M. B., Delfabbro, P. H., Burns, N. R., & Begg, S. H. (2014). Individual differences in anchoring: Traits and experience. Learning and Individual Differences, 29, 131-140.

Yousaf, Z., Siddiqui, M. Y. A., Mushtaq, K., Feroz, S. E., Abou Kammar, S., Mohamedali, M. G. H., & Chaudhary, H. (2020). Avoiding anchoring bias in the times of the pandemic!. Case Reports in Neurology, 12 (3), 359-364.

Saul Mcleod, PhD

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Educator, Researcher

Saul Mcleod, Ph.D., is a qualified psychology teacher with over 18 years experience of working in further and higher education.

Eleanor Myers

Research Assistant at Princeton University

Psychology Undergraduate, Princeton University

Eleanor Myers is a senior psychology major at Princeton University.  She studies language development as a research assistant in the Princeton Baby Lab.