Regression toward the mean in the context of "Attribute substitution"

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⭐ Core Definition: Regression toward the mean

In statistics, regression toward the mean (also called regression to the mean, reversion to the mean, and reversion to mediocrity) is the phenomenon where if one sample of a random variable is extreme, the next sampling of the same random variable is likely to be closer to its mean. Furthermore, when many random variables are sampled and the most extreme results are intentionally picked out, it refers to the fact that (in many cases) a second sampling of these picked-out variables will result in "less extreme" results, closer to the initial mean of all of the variables.

Mathematically, the strength of this "regression" effect is dependent on whether or not all of the random variables are drawn from the same distribution, or if there are genuine differences in the underlying distributions for each random variable. In the first case, the "regression" effect is statistically likely to occur, but in the second case, it may occur less strongly or not at all.

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👉 Regression toward the mean in the context of Attribute substitution

Attribute substitution is a psychological process thought to underlie a number of cognitive biases and perceptual illusions. It occurs when an individual has to make a judgment (of a target attribute) that is computationally complex, and instead substitutes a more easily calculated heuristic attribute. This substitution is thought of as taking place in the automatic intuitive judgment system, rather than the more self-aware reflective system. Hence, when someone tries to answer a difficult question, they may actually answer a related but different question, without realizing that a substitution has taken place. This explains why individuals can be unaware of their own biases, and why biases persist even when the subject is made aware of them. It also explains why human judgments often fail to show regression toward the mean.

The theory of attribute substitution unifies a number of separate explanations of reasoning errors in terms of cognitive heuristics. In turn, the theory is subsumed by an effort-reduction framework proposed by Anuj K. Shah and Daniel M. Oppenheimer, which states that people use a variety of techniques to reduce the effort of making decisions.

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Regression toward the mean in the context of Francis Galton

Sir Francis Galton FRS FRAI (/ˈɡɔːltən/; 16 February 1822 – 17 January 1911) was an English polymath and the originator of eugenics during the Victorian era; his ideas later became the basis of behavioural genetics.

Galton produced over 340 papers and books. He also developed the statistical concept of correlation and widely promoted regression toward the mean. He was the first to apply statistical methods to the study of human differences and inheritance of intelligence, and introduced the use of questionnaires and surveys for collecting data on human communities, which he needed for genealogical and biographical works and for his anthropometric studies. He popularised the phrase "nature versus nurture". His book Hereditary Genius (1869) was the first social scientific attempt to study genius and greatness.

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Regression toward the mean in the context of Heightism

Height discrimination is prejudice or discrimination against individuals based on height. In principle, it refers to the discriminatory treatment against individuals whose height is not within the normal acceptable range of height in a population. Various studies have shown it to be a cause of bullying, commonly manifested as unconscious microaggressions.

Modern Western height discrimination originated in 19th century eugenic, Social Darwinist, and white supremacist movements, beginning with eugenicist Sir Francis Galton's observation of the correlation of human height between parents and offspring. These movements promulgated pseudoscientific beliefs about the superiority of larger male stature, most grotesquely embodied by the Nazi height ideals within the social construct of the Aryan master race.

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