Home » 14 Biases which lead us to make stories when we look at sparse data

14 Biases which lead us to make stories when we look at sparse data

We tend to find stories and data when looking at sparse data.

Since we only get a tiny sliver of the world’s information, and also filter out almost everything else, we never have the luxury of having the full story. This is how our brain reconstructs the world to feel complete inside our heads.

Confabulation

A disturbance of memory, defined as the production of fabricated, distorted, or misinterpreted memories about oneself or the world, without the conscious intention to deceive. People who confabulate present incorrect memories ranging from subtle alterations to bizarre fabrications, and are generally very confident about their recollections, despite contradictory evidence.

Clustering Illusion

The tendency to erroneously consider the inevitable streaks or clusters arising in small samples from random distributions to be non-random. The illusion is caused by a human tendency to underpredict the amount of variability likely to appear in a small sample of random or semi-random data. Read More.

Insensitivity to Sample Size

A cognitive bias that occurs when people judge the probability of obtaining a sample statistic without respect to the sample size. For example, in one study subjects assigned the same probability to the likelihood of obtaining a mean height of above six feet in samples of 10, 100, and 1,000 men. In other words, variation is more likely in smaller samples, but people do not expect this.

Neglect of Probability

The tendency to disregard probability when making a decision under uncertainty. It is one way in which people regularly violate the normative rules for decision making. Small risks are typically either neglected entirely or hugely overrated. The continuum between the extremes is ignored. There are many related ways in which people violate the normative rules of decision making with regard to probability including hindsight bias, the neglect of prior base rates effect, and the gambler’s fallacy. However, this bias is different in that rather than incorrectly using probability, the actor disregards it. Read More.

Anecdotal Fallacy

Misuse of anecdotal evidence is an informal fallacy and is sometimes referred to as the “person who” fallacy (“1 know a person who…”; “I know of a case where…” etc.) which places undue weight on experiences of close peers which may not be typical.

A common way anecdotal evidence becomes unscientific is through fallacious reasoning such as the Post hoc ergo propter hoc fallacy, the human tendency to assume that if one event happens after another, then the first must be the cause of the second. Another fallacy involves inductive reasoning. For instance, if an anecdote illustrates a desired conclusion rather than a logical conclusion, it is considered a faulty or hasty generalization.

Illusion of Validity

A cognitive bias in which a person overestimates his or her ability to interpret and predict accurately the outcome when analyzing a set of data, in particular when the data analyzed show a very consistent pattern—that is, when the data “tell” a coherent story. This effect persists even when the person is aware of all the factors that limit the accuracy of his or her predictions, that is when the data and/or methods used to judge them lead to highly fallible predictions. Example. Subjects reported higher confidence in a prediction of the final grade point average of a student after seeing a first-year record of consistent B’s than a first-year record of an even number of As and Cs. Consistent patterns may be observed when input variables are highly redundant or correlated, which may increase subjective confidence. However, a number of highly correlated inputs should not increase confidence much more than only one of the inputs; instead higher confidence should be merited when a number of highly independent inputs show a consistent pattern.

Related. WYSIATI (What You See Is All There Is) This is solving a difficult problem by substituting a simpler problem that you know about. One does not solve the other.

Masked Man Fallacy (Intentional Fallacy, Epistemic Fallacy)

The masked-man fallacy is committed when one makes an illicit use (illicit due to the difference between knowing and being, knowing can be subject to error or incompleteness) of Leibniz’s law in an argument. Leibniz’s law states that, if one object has a certain property, while another object does not have the same property, the two objects cannot be identical.

Example. Premise 1 I know who Bob is.

Premise 2 I do not know who the masked man is.

Conclusion – Therefore, Bob is not the masked man.

The premises may be true and the conclusion false if Bob is the masked man and the speaker does not know that. Thus the argument is a fallacious one.

Recency Illusion

The belief that things you have noticed only recently are in fact recent.

Gambler’s Fallacy (Monte Carlo Fallacy, Fallacy of the Maturity of Chances)

The mistaken belief that, if something happens more frequently than normal during some period, it will happen less frequently in the future or that if something happens less frequently than normal during some period, it will happen more frequently in the future (presumably as a means of balancing nature). Read More.

Hot Hand Fallacy (Hot Hand Phenomenon, Hot Hand)

The sometimes fallacious belief that a person who experiences success with a random event has a greater probability of further success in additional attempts. This is written as “sometimes” because a quasi-random event that involves skill, such as basketball free-throws, may be susceptible to the psychological effect of believing a continued outcome; and therefore an aspect of the “Hot Hand” may be true.

Illusory Correlation

The phenomenon of perceiving a relationship between variables (typically people, events, or behaviors) even when no such relationship exists. A false association may be formed because rare or novel occurrences are more salient and therefore tend to capture one’s attention.

Example. A woman has her purse stolen by a person of a specific demographic. Henceforth, she keeps her close purse each time she sees a similar person. Example. A man holds the belief that people in urban environments tend to be rude. Therefore, when he meets someone who is rude he assumes that the person lives in a city, rather than a rural area.

Pareidolia (Subset of Apophenia)

A psychological phenomenon in which the mind responds to a stimulus, usually an image or a sound, by perceiving a familiar pattern where none exists (e.g., in random data).

– Apophenia

A human tendency to seek patterns in random information.

– Anthropomorphism

The attribution of human traits, emotions, or intentions to non-human entities.

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