Intelligence quotient

Overview


An intelligence quotient or IQ is a score derived from one of several different standardized tests attempting to measure intelligence. IQ tests are used as predictors of educational achievement. People with low IQ scores are sometimes placed in special-needs education.

IQ scores are also used by social scientists; in particular, they study the distribution of IQ scores in populations and the relationships between IQ score and other variables. IQ correlates with job performance and income, also with the social status of the parents. Recent work has demonstrated links between IQ and both morbidity and mortality. While IQ heritability has been investigated for nearly a century, controversy remains as to how much is heritable, and the mechanisms for heritability are still a matter of some debate. The same study suggests that the heritable component of IQ becomes more significant with age. The average IQ scores for many populations were rising at an average rate of three points per decade during the 20th century with most of the increase in the lower half of the IQ range: a phenomenon called the Flynn effect. It is disputed whether these changes in scores reflect real changes in intellectual abilities, or merely methodological problems with past testing.

History
In 1905 the French psychologist Alfred Binet published the first modern intelligence test, the Binet-Simon intelligence scale. His principal goal was to identify students who needed special help in coping with the school curriculum. Along with his collaborator Theodore Simon, Binet published revisions of his intelligence scale in 1908 and 1911, the last appearing just before his untimely death.

In 1912, the abbreviation of "intelligence quotient" or I.Q., a translation of the German Intelligenz-Quotient, was coined by the German psychologist William Stern. A further refinement of the Binet-Simon scale was published in 1916 by Lewis M. Terman, from Stanford University, who incorporated Stern's proposal that an individual's intelligence level be measured as an intelligence quotient (I.Q.). Terman's test, which he named the Stanford-Binet Intelligence Scale formed the basis for one of the modern intelligence tests still commonly used today.

Originally, IQ was calculated as a ratio with the formula $$100 \times \frac{\text{mental age}}{\text{chronological age}}.$$

A 10-year-old who scored as high as the average 13-year-old, for example, would have an IQ of 130 (100*13/10).

In 1939 David Wechsler published the first intelligence test explicitly designed for an adult population, the Wechsler Adult Intelligence Scale, or WAIS. Since publication of the WAIS, Wechsler extended his scale downward to create the Wechsler Intelligence Scale for Children, or WISC, which is still in common usage. The Wechsler scales contained separate subscores for verbal and performance IQ, thus being less dependent on overall verbal ability than early versions of the Stanford-Binet scale, and was the first intelligence scale to base scores on a standardized normal distribution rather than an age-based quotient.

Because age-based quotients only worked for children, it was replaced by a projection of the measured rank on the Gaussian bell curve with a center value (average IQ) of 100, and a standard deviation of 15 or occasionally 16 or 24. Thus the modern version of the IQ is a mathematical transformation of a raw score (based on the rank of that score in a normalization sample; see quantile, percentile, percentile rank), which is the primary result of an IQ test. To differentiate the two scores, modern scores are sometimes referred to as "deviance IQ", while the age-specific scores are referred to as "ratio IQ". While the two methodologies yield similar results near the middle of the bell curve, the older ratio IQs yielded far higher scores for the intellectually gifted&mdash;Marilyn vos Savant appeared in the Guinness Book of World Records for obtaining a ratio IQ of 228. While this score could make sense using Binet's formula (and even then, only for a child), on the Gaussian curve model it would be an exceptional 7.9 standard deviations above the mean and hence virtually impossible in a population with a normal IQ distribution (see normal distribution). In addition, IQ tests like the Wechsler were not intended to reliably discriminate much beyond IQ 130, as they simply do not contain enough exceptionally difficult items.

Since the publication of the WAIS, almost all intelligence scales have adopted the normal distribution method of scoring. The use of the normal distribution scoring method makes the term "intelligence quotient" an inaccurate description of the intelligence measurement, but I.Q. still enjoys colloquial usage, and is used to describe all of the intelligence scales currently in use.

IQ Test Structure
IQ tests come in many forms, and some tests use a single type of item or question, while others use several different subtests. Most tests yield both an overall score and individual subtest scores.

A typical IQ test requires the test subject to solve a fair number of problems in a set time under supervision. Most IQ tests include items from various domains, such as short-term memory, verbal knowledge, spatial visualization, and perceptual speed. Some tests have a total time limit, others have a time limit for each group of problems, and there are a few untimed, unsupervised tests, typically geared to measuring high intelligence. The most widely used standardized test for determining IQ is the WAIS (Wechsler Adult Intelligence Scale). The WAIS III consists of fourteen subtests, seven verbal (information, comprehension, numerical reasoning, similarities, digit memory, letter-number sequencing, and vocabulary) and seven performance (digit symbol-coding, picture completion, block design, matrix reasoning, picture arrangement, symbol search, and object assembly).

When standardizing an IQ test, a representative sample of the population is tested using each test question. IQ tests are calibrated in such a way as to yield a normal distribution, or "bell curve".

Each IQ test, however, is designed and valid only for a certain IQ range. Because so few people score in the extreme ranges, IQ tests usually cannot accurately measure very low and very high IQs.

Various IQ tests measure a standard deviation with different number of points. Thus, when an IQ score is stated, the standard deviation used should also be stated.

Where an individual has scores that do not correlate with each other, there is a good reason to look for a learning disability or other cause for the lack of correlation. Tests have been chosen for inclusion because they display the ability to use this method to predict later difficulties in learning.

Different individuals exhibit different IQ scores, depending on the individual these may or not be stable over their lifetime

Reference charts
IQ reference charts are tables, suggested by psychologists to divide intelligence ranges in various categories.

High IQ societies
A high IQ society is an organization that limits membership to people who are within a certain high percentile of IQ test results. The most well-known is Mensa International, which requires members to score in the top 2% of a standardized IQ test.

IQ and general intelligence factor
Modern IQ tests produce scores for different areas (e.g., language fluency, three-dimensional thinking), with the summary score calculated from subtest scores. The average score, according to the bell curve, is 100. Individual subtest scores tend to correlate with one another, even when seemingly disparate in content.

Mathematical analysis of individuals' scores on the subtests of a single IQ test or the scores from a variety of different IQ tests (e.g., Stanford-Binet, WISC-R, Raven's Progressive Matrices, Cattell Culture Fair III, Universal Nonverbal Intelligence Test, Primary Test of Nonverbal Intelligence, and others) find that they can be described mathematically as measuring a single common factor and various factors that are specific to each test. This kind of factor analysis has led to the theory that underlying these disparate cognitive tasks is a single factor, termed the general intelligence factor (or g), that corresponds with the common-sense concept of intelligence. In the normal population, g and IQ are roughly 90% correlated and are often used interchangeably.

Tests differ in their g-loading, which is the degree to which the test score reflects g rather than a specific skill or "group factor" (such as verbal ability, spatial visualization, or mathematical reasoning). g-loading and validity have been observed to be related in the sense that most IQ tests derive their validity mostly or entirely from the degree to which they measure g.

Heritability
The role of genes and environment (nature and nurture) in determining IQ is reviewed in Plomin et al. (2001, 2003). . Until recently heritability was mostly studied in children. Various studies find the heritability of IQ between 0.4 and 0.8 in the United States; that is, depending on the study, a little less than half to substantially more than half of the variation in IQ among the children studied was due to variation in their genes. The remainder was thus due to environmental variation and measurement error. A heritability in the range of 0.4 to 0.8 implies that IQ is "substantially" heritable.

The effect of restriction of range on IQ was examined by Matt McGue and colleagues, who write that "restriction in range in parent disinhibitory psychopathology and family SES had no effect on adoptive-sibling correlations ... IQ". On the other hand, a 2003 study by Eric Turkheimer, Andreana Haley, Mary Waldron, Brian D'Onofrio, Irving I. Gottesman demonstrated that the proportions of IQ variance attributable to genes and environment vary with socioeconomic status. They found that in impoverished families, 60% of the variance in IQ is accounted for by the shared environment, and the contribution of genes was close to zero.

It is reasonable to expect that genetic influences on traits like IQ should become less important as one gains experiences with age. Surprisingly, the opposite occurs. Heritability measures in infancy are as low as 20%, around 40% in middle childhood, and as high as 80% in adulthood. The American Psychological Association's 1995 task force on "Intelligence: Knowns and Unknowns" concluded that within the white population the heritability of IQ is "around .75". The Minnesota Study of Twins Reared Apart, a multiyear study of 100 sets of reared-apart twins which was started in 1979, concluded that about 70% of the variance in IQ was found to be associated with genetic variation. Some of the correlation of IQs of twins may be a result of the effect of the maternal environment before birth, shedding some light on why IQ correlation between twins reared apart is so robust.

There are a number of points to consider when interpreting heritability:
 * A high heritability does not mean that the environment has no effect on the development of a trait, or that learning is not involved. Vocabulary size, for example, is very substantially heritable (and highly correlated with general intelligence) although every word in an individual's vocabulary is learned. In a society in which plenty of words are available in everyone's environment, especially for individuals who are motivated to seek them out, the number of words that individuals actually learn depends to a considerable extent on their genetic predispositions..
 * A common error is to assume that because something is heritable it is necessarily unchangeable. This is wrong. Heritability does not imply immutability. As previously noted, heritable traits can depend on learning, and they may be subject to other environmental effects as well. The value of heritability can change if the distribution of environments (or genes) in the population is substantially altered. For example, an impoverished or suppressive environment could fail to support the development of a trait, and hence restrict individual variation. Differences in variation of heritability are found between developed and developing nations. This could affect estimates of heritability. Another example is Phenylketonuria which previously caused mental retardation for everyone who had this genetic disorder. Today, this can be prevented by following a modified diet.
 * On the other hand, there can be effective environmental changes that do not change heritability at all. If the environment relevant to a given trait improves in a way that affects all members of the population equally, the mean value of the trait will rise without any change in its heritability (because the differences among individuals in the population will stay the same). This has evidently happened for height: the heritability of stature is high, but average heights continue to increase.
 * Even in developed nations, high heritability of a trait within a given group has no necessary implications for the source of a difference between groups.

Environment
Environmental factors play a role in determining IQ. Proper childhood nutrition appears critical for cognitive development; malnutrition can lower IQ. Other research indicates environmental factors such as prenatal exposure to toxins, duration of breastfeeding, and micronutrient deficiency can affect IQ.

It is well known that it is possible to increase one's IQ score by training, for example by regularly playing puzzle games, or strategy games like Chess. Musical training in childhood also increases IQ. Recent studies have shown that training in using one's working memory may increase IQ.

Family environment
In the developed world, nearly all personality traits show that, contrary to expectations, environmental effects actually cause non-related children raised in the same family ("adoptive siblings") to be as different as children raised in different families. There are some family effects on the IQ of children, accounting for up to a quarter of the variance. However, by adulthood, this correlation disappears, such that adoptive siblings are not more similar in IQ than strangers. For IQ, adoption studies show that, after adolescence, adoptive siblings are no more similar in IQ than strangers (IQ correlation near zero), while full siblings show an IQ correlation of 0.6. Twin studies reinforce this pattern: monozygotic (identical) twins raised separately are highly similar in IQ (0.86), more so than dizygotic (fraternal) twins raised together (0.6) and much more than adoptive siblings (~0.0). The American Psychological Association's report Intelligence: Knowns and Unknowns (1995) states that there is no doubt that normal child development requires a certain minimum level of responsible care. Severely deprived, neglectful, or abusive environments must have negative effects on a great many aspects of development, including intellectual aspects. Beyond that minimum, however, the role of family experience is in serious dispute. Do differences between children's family environments (within the normal range) produce differences in their intelligence test performance? The problem here is to disentangle causation from correlation. There is no doubt that such variables as resources of the home and parents' use of language are correlated with children's IQ scores, but such correlations may be mediated by genetic as well as (or instead of) environmental factors. But how much of that variance in IQ results from differences between families, as contrasted with the varying experiences of different children in the same family? Recent twin and adoption studies suggest that while the effect of the family environment is substantial in early childhood, it becomes quite small by late adolescence. These findings suggest that differences in the life styles of families whatever their importance may be for many aspects of children's lives make little long-term difference for the skills measured by intelligence tests. It also stated "We should note, however, that low-income and non-white families are poorly represented in existing adoption studies as well as in most twin samples. Thus it is not yet clear whether these studies apply to the population as a whole. It remains possible that, across the full range of income and ethnicity, between-family differences have more lasting consequences for psychometric intelligence."

A study of French children adopted between the ages of 4 and 6 shows the continuing interplay of nature and nurture. The children came from poor backgrounds with IQs that initially averaged 77, putting them near retardation. Nine years later after adoption, they retook the I.Q. tests, and all of them did better. The amount they improved was directly related to the adopting family’s status. "Children adopted by farmers and laborers had average I.Q. scores of 85.5; those placed with middle-class families had average scores of 92. The average I.Q. scores of youngsters placed in well-to-do homes climbed more than 20 points, to 98." On the other hand, the degree to which these increases persisted into adulthood are not clear from the study.

Biased older studies?
Stoolmiller (1999) found that the range restriction of family environments that goes with adoption, that adopting families tend to be more similar on for example socio-economic status than the general population, means that role of the shared family environment have been underestimated in previous studies. Corrections for range correction applied to adoption studies indicate that socio-economic status could account for as much as 50% of the variance in IQ. However, the effect of restriction of range on IQ for adoption studies was examined by Matt McGue and colleagues, who wrote that "restriction in range in parent disinhibitory psychopathology and family socio-economic status had no effect on adoptive-sibling correlations [in] IQ".

Eric Turkheimer and colleagues (2003), not using an adoption study, included impoverished US families. Results demonstrated that the proportions of IQ variance attributable to genes and environment vary nonlinearly with socio-economic status. The models suggest that in impoverished families, 60% of the variance in IQ is accounted for by the shared family environment, and the contribution of genes is close to zero; in affluent families, the result is almost exactly the reverse. They suggest that the role of shared environmental factors may have been underestimated in older studies which often only studied affluent middle class families.

Maternal (fetal) environment
A meta-analysis, by Devlin and colleagues in Nature (1997), of 212 previous studies evaluated an alternative model for environmental influence and found that it fits the data better than the 'family-environments' model commonly used. The shared maternal (fetal) environment effects, often assumed to be negligible, account for 20% of covariance between twins and 5% between siblings, and the effects of genes are correspondingly reduced, with two measures of heritability being less than 50%. They argue that the shared maternal environment may explain the striking correlation between the IQs of twins, especially those of adult twins that were reared apart.

Bouchard and McGue reviewed the literature in 2003, arguing that Devlin's conclusions about the magnitude of heritability is not substantially different than previous reports and that their conclusions regarding prenatal effects stands in contradiction to many previous reports. They write that: "Chipuer et al. and Loehlin conclude that the postnatal rather than the prenatal environment is most important. The Devlin et al conclusion that the prenatal environment contributes to twin IQ similarity is especially remarkable given the existence of an extensive empirical literature on prenatal effects. Price (1950),  in a comprehensive review published over 50 years ago, argued that almost all MZ twin prenatal effects produced differences rather than similarities. As of 1950 the literature on the topic was so large that the entire bibliography was not published. It was finally published in 1978 with an additional 260 references. At that time Price reiterated his earlier conclusion  . Research subsequent to the 1978 review largely reinforces Price’s hypothesis ("

The Dickens and Flynn model
Dickens and Flynn (2001) postulate that the arguments regarding the disappearance of the shared family environment should apply equally well to groups separated in time. This is contradicted by the Flynn effect. Changes here have happened too quickly to be explained by genetics. This paradox can be explained by observing that the measure "heritability" includes both a direct effect of the genotype on IQ and also indirect effects where the genotype changes the environment, in turn affecting IQ. That is, those with a higher IQ tend to seek out stimulating environments that further increase IQ. The direct effect can initially have been very small but feedback loops can create large differences in IQ. In their model an environmental stimulus can have a very large effect on IQ, even in adults, but this effect also decays over time unless the stimulus continues (the model could be adapted to include possible factors, like nutrition in early childhood, that may cause permanent effects). The Flynn effect can be explained by a generally more stimulating environment for all people. The authors suggest that programs aiming to increase IQ would be most likely to produce long-term IQ gains if they taught children how to replicate outside the program the kinds of cognitively demanding experiences that produce IQ gains while they are in the program and motivate them to persist in that replication long after they have left the program.

Mental handicaps
Individuals with an unusually low IQ score, varying from about 70 ("Educable Mentally Retarded") to as low as 20 (usually caused by a neurological condition), are considered developmental difficulties. However, there is no true IQ-based classification for developmental disabilities.

IQ and the brain
In 2004, Richard Haier, professor of psychology in the Department of Pediatrics and colleagues at University of California, Irvine and the University of New Mexico used MRI to obtain structural images of the brain in 47 normal adults who also took standard IQ tests. The study demonstrated that general human intelligence appears to be based on the volume and location of gray matter tissue in the brain. Regional distribution of gray matter in humans is highly heritable. The study also demonstrated that, of the brain's gray matter, only about 6 percent appeared to be related to IQ.

Many different sources of information have converged on the view that the frontal lobes are critical for fluid intelligence. Patients with damage to the frontal lobe are impaired on fluid intelligence tests (Duncan et al 1995). The volume of frontal grey (Thompson et al 2001) and white matter (Schoenemann et al 2005) have also been associated with general intelligence. In addition, recent neuroimaging studies have limited this association to the lateral prefrontal cortex. Duncan and colleagues (2000) showed using Positron Emission Tomography that problem-solving tasks that correlated more highly with IQ also activate the lateral prefrontal cortex. More recently, Gray and colleagues (2003) used functional magnetic resonance imaging (fMRI) to show that those individuals that were more adept at resisting distraction on a demanding working memory task had both a higher IQ and increased prefrontal activity. For an extensive review of this topic, see Gray and Thompson (2004).

A study involving 307 children (age between six to nineteen) measuring the size of brain structures using magnetic resonance imaging (MRI) and measuring verbal and non-verbal abilities has been conducted (Shaw et al 2006). The study has indicated that there is a relationship between IQ and the structure of the cortex—the characteristic change being the group with the superior IQ scores starts with thinner cortex in the early age then becomes thicker than average by the late teens.

Significant injuries isolated to one side of the brain, even those occurring at a young age, may not significantly affect IQ.

Studies reach conflicting conclusions regarding the controversial idea that brain size correlates positively with IQ. Jensen and Reed (1993) claim no direct correlation exists in nonpathological subjects. A more recent meta-analysis suggests otherwise.

An alternative approach has sought to link differences in neural plasticity with intelligence (Garlick, 2002 ), and this view has recently received some empirical support (Shaw et al., 2006 ).

The Flynn effect
The Flynn effect is named after James R. Flynn, a New Zealand based political scientist. He discovered that IQ scores worldwide appear to be slowly rising at a rate of around three IQ points per decade. Attempted explanations have included improved nutrition, a trend towards smaller families, better education, greater environmental complexity, and heterosis. Tests are therefore renormalized occasionally to obtain mean scores of 100, for example WISC-R (1974), WISC-III (1991) and WISC-IV (2003). Hence it is difficult to compare IQ scores measured years apart, unless this is compensated for.

The Flynn effect may have ended in some developed nations starting in the mid 1990s. Teasdale & Owen (2005) "report intelligence test results from over 500,000 young Danish men, tested between 1959 and 2004, showing that performance peaked in the late 1990s, and has since declined moderately to pre-1991 levels." They speculate that "a contributing factor in this recent fall could be a simultaneous decline in proportions of students entering 3-year advanced-level school programs for 16–18 year olds."

In 2004, Jon Martin Sundet of the University of Oslo and colleagues published an article documenting scores on intelligence tests given to Norwegian conscripts between the 1950s and 2002, showing that the increase in scores of general intelligence stopped after the mid-1990s and in numerical reasoning subtests, declined.

Group differences
Among the most controversial issues related to the study of intelligence is the observation that intelligence measures such as IQ scores vary between populations. While there is little scholarly debate about the existence of some of these differences, the reasons remain highly controversial both within academia and in the public sphere.

Health and IQ
Several factors can lead to significant cognitive impairment, particularly if they occur during pregnancy and childhood when the brain is growing and the blood-brain barrier is less effective. Such impairment may sometimes be permanent, or may sometimes be partially or wholly compensated for by later growth. Several harmful factors may also combine, possibly causing greater impairment.

Developed nations have implemented several health policies regarding nutrients and toxins known to influence cognitive function. These include laws requiring fortification of certain food products and laws establishing safe levels of pollutants (e.g. lead, mercury, and organochlorides). Comprehensive policy recommendations targeting reduction of cognitive impairment in children have been proposed.

In terms of the effect of one's intelligence on health, high childhood IQ correlates with one's chance of becoming a vegetarian in adulthood, and inversely correlates with the chances of smoking , becoming obese, and having serious traumatic accidents in adulthood.

Sex and IQ
Most studies claim that despite sometimes significant differences in subtest scores, men and women have quite similar average IQ. Some studies claim that men outperform women on average by 3-4 IQ points. Some studies claim that women perform better on tests of memory and verbal proficiency, for example, while men perform better on tests of mathematical and spatial ability. Male scores display a higher variance: there are more men than women identified with both very high and very low IQs.

Race and IQ
Much research has been devoted to the extent and potential causes of racial group differences in IQ.

Positive correlations with IQ
While IQ is sometimes treated as an end unto itself, scholarly work on IQ focuses to a large extent on IQ's validity, that is, the degree to which IQ correlates with outcomes such as job performance, social pathologies, or academic achievement. Different IQ tests differ in their validity for various outcomes. Traditionally, correlation for IQ and outcomes is viewed as a means to also predict performance; however, because IQ is a known social artifact, readers should distinguish between prediction in the hard sciences and the social sciences.

Validity is the correlation between score (in this case cognitive ability, as measured, typically, by a paper-and-pencil test) and outcome (in this case job performance, as measured by a range of factors including supervisor ratings, promotions, training success, and tenure), and ranges between −1.0 (the score is perfectly wrong in predicting outcome) and 1.0 (the score perfectly predicts the outcome). See validity (psychometric).

Research shows that general intelligence plays an important role in many valued life outcomes. In addition to academic success, IQ correlates to some degree with job performance (see below), socioeconomic advancement (e.g., level of education, occupation, and income), and "social pathology" (e.g., adult criminality, poverty, unemployment, dependence on welfare, children outside of marriage). Recent work has demonstrated links between general intelligence and health, longevity, and functional literacy. Correlations between g and life outcomes are pervasive, though IQ does not correlate with subjective self-reports of happiness. IQ and g correlate highly with school performance and job performance, less so with occupational prestige, moderately with income, and to a small degree with law-abiding behaviour. IQ does not explain the inheritance of economic status and wealth.

Other tests
One study found a correlation of .82 between g and SAT scores. Another correlation of .81 between g and GCSE scores.

Correlations between IQ scores (general cognitive ability) and achievement test scores are reported to be .81 by Deary and colleagues, with the percentage of variance accounted for by general cognitive ability ranging "from 58.6% in Mathematics and 48% in English to 18.1% in Art and Design"

School performance
The American Psychological Association's report Intelligence: Knowns and Unknowns (1995) Wherever it has been studied, children with high scores on tests of intelligence tend to learn more of what is taught in school than their lower-scoring peers. The correlation between IQ scores and grades is about .50. However, this means that they explain only 25% of the variance. Successful school learning depends on many personal characteristics other than intelligence, such as memory, persistence, interest in school, and willingness to study.

Correlations between IQ scores and total years of education are about .55, implying that differences in psychometric intelligence account for about 30% of the outcome variance. Many occupations can only be entered through professional schools which base their admissions at least partly on test scores: the MCAT, the GMAT, the GRE, the DAT, the LSAT, etc. Individual scores on admission-related tests such as these are certainly correlated with scores on tests of intelligence. It is partly because intelligence test scores predict years of education that they also predict occupational status, and income to a smaller extent.

Job performance
According to Schmidt and Hunter, "for hiring employees without previous experience in the job the most valid predictor of future performance is general mental ability." The validity depends on the type of job and varies across different studies, ranging from 0.2 to 0.6. However IQ mostly correlates with cognitive ability only if IQ scores are below average and this rule has many (about 30 %) exceptions for people with average and higher IQ scores. Also, IQ is related to the "academic tasks" (auditory and linguistic measures, memory tasks, academic achievement levels) and much less related to tasks where even precise hand work ("motor functions") are required

A meta-analysis (Hunter and Hunter, 1984) which pooled validity results across many studies encompassing thousands of workers (32,124 for cognitive ability), reports that the validity of cognitive ability for entry-level jobs is 0.54, larger than any other measure including job try-out (0.44), experience (0.18), interview (0.14), age (−0.01), education (0.10), and biographical inventory (0.37). This implies that, across a wide range of occupations, intelligence test performance accounts for some 29% of the variance in job performance.

According to Marley Watkins and colleagues, IQ is a causal influence on future academic achievement, whereas academic achievement does not substantially influence future IQ scores. Treena Eileen Rohde and Lee Anne Thompson write that general cognitive ability but not specific ability scores predict academic achievement, with the exception that processing speed and spatial ability predict performance on the SAT math beyond the effect of general cognitive ability.

The American Psychological Association's report Intelligence: Knowns and Unknowns (1995) states that other individual characteristics such as interpersonal skills, aspects of personality, etc., are probably of equal or greater importance, but at this point we do not have equally reliable instruments to measure them.

Income
Some researchers claim that "in economic terms it appears that the IQ score measures something with decreasing marginal value. It is important to have enough of it, but having lots and lots does not buy you that much."

Other studies show that ability and performance for jobs are linearly related, such that at all IQ levels, an increase in IQ translates into a concomitant increase in performance. Charles Murray, coauthor of The Bell Curve, found that IQ has a substantial effect on income independently of family background.

The American Psychological Association's report Intelligence: Knowns and Unknowns (1995) states that IQ scores account for about one-fourth of the social status variance and one-sixth of the income variance. Statistical controls for parental SES eliminate about a quarter of this predictive power. Psychometric intelligence appears as only one of a great many factors that influence social outcomes.

One reason why some studies claim that IQ only accounts for a sixth of the variation in income is because many studies are based on young adults (many of whom have not yet completed their education). On pg 568 of The g factor, Arthur Jensen claims that although the correlation between IQ and income averages a moderate 0.4 (one sixth or 16% of the variance), the relationship increases with age, and peaks at middle age when people have reached their maximum career potential. In the book, a Question of Intelligence, Danial Seligman cites an IQ income correlation of 0.5 (25% of the variance).

A 2002 study further examined the impact of non-IQ factors on income and concluded that an offspring's inherited wealth, race, and schooling are more important as factors in determining income than IQ.

Other effects
In addition, IQ and its correlation to health, violent crime, gross state product, and government effectiveness are the subject of a 2006 paper in the publication Intelligence. The paper breaks down IQ averages by U.S. states using the federal government's National Assessment of Educational Progress math and reading test scores as a source.

There is a correlation of -.19 between IQ scores and number of juvenile offences in a large Danish sample; with social class controlled, the correlation dropped to -. 17. Similarly, the correlations for most "negative outcome" variables are typically smaller than .20, which means that test scores are associated with less than 4% of their total variance. It is important to realize that the causal links between psychometric ability and social outcomes may be indirect. Children who are unsuccessful in - and hence alienated from - school may be more likely to engage in delinquent behaviours for that very reason, compared to other children who enjoy school and are doing well.

IQ is also associated with certain diseases.

The book IQ and the Wealth of Nations claims to show that the GDP/person of a nation can in large part be explained by the average IQ score of its citizens. This claim has been both disputed and supported in peer-reviewed papers. The data used have also been questioned.

Tambs et al. (1989) found that occupational status, educational attainment, and IQ are individually heritable; and further found that "genetic variance influencing educational attainment … contributed approximately one-fourth of the genetic variance for occupational status and nearly half the genetic variance for IQ". In a sample of U.S. siblings, Rowe et al. (1997) report that the inequality in education and income was predominantly due to genes, with shared environmental factors playing a subordinate role.

Some argue that IQ scores are used as an excuse for not trying to reduce poverty or otherwise improve living standards for all. Claimed low intelligence has historically been used to justify the feudal system and unequal treatment of women (but note that many studies find identical average IQs among men and women; see sex and intelligence). In contrast, others claim that the refusal of "high-IQ elites" to take IQ seriously as a cause of inequality is itself immoral.

Public policy
In the United States, certain public policies and laws regarding military service, education, public benefits, crime, and employment incorporate an individual's IQ or similar measurements into their decisions. However, in 1971 the U.S. Supreme Court had banned the use of IQ tests in employment, except in very rare cases. Internationally, certain public policies, such as improving nutrition and prohibiting neurotoxins, have as one of their goals raising or preventing a decline in intelligence.

The view of the American Psychological Association
In response to the controversy surrounding The Bell Curve, the American Psychological Association's Board of Scientific Affairs established a task force in 1995 to write a consensus statement on the state of intelligence research which could be used by all sides as a basis for discussion. The full text of the report is available at a third-party website. .

In this paper the representatives of the association regret that IQ - related works are frequently written with a view to their political consequences and possible impact on the society. As researchers, they feel no responsibility for this and would like to concentrate on the purely scientific side of the question ("research findings were often assessed not so much on their merits or their scientific standing as on their supposed political implications").

The findings of the task force state that IQ scores do have high predictive validity for individual differences in school achievement. They confirm the predictive validity of IQ for adult occupational status, even when variables such as education and family background have been statistically controlled. They agree that individual (but specifically not population) differences in intelligence are substantially influenced by genetics.

They state there is little evidence to show that childhood diet influences intelligence except in cases of severe malnutrition. They agree that there are no significant differences between the average IQ scores of males and females. The task force agrees that large differences do exist between the average IQ scores of blacks and whites, and that these differences cannot be attributed to biases in test construction. While they admit there is no empirical evidence supporting it, the APA task force suggests that explanations based on social status and cultural differences may be possible. Regarding genetic causes, they noted that there is not much direct evidence on this point, but what little there is fails to support the genetic hypothesis.

The APA journal that published the statement, American Psychologist, subsequently published eleven critical responses in January 1997, several of them arguing that the report failed to examine adequately the evidence for partly-genetic explanations.

Binet
Alfred Binet did not believe that IQ test scales qualified to measure intelligence. He neither invented the term "intelligence quotient" nor supported its numerical expression. He stated:


 * The scale, properly speaking, does not permit the measure of intelligence, because intellectual qualities are not superposable, and therefore cannot be measured as linear surfaces are measured. (Binet 1905)

Binet had designed the Binet-Simon intelligence scale in order to identify students who needed special help in coping with the school curriculum. He argued that with proper remedial education programs, most students regardless of background could catch up and perform quite well in school. He did not believe that intelligence was a measurable fixed entity.

Binet cautioned:


 * Some recent thinkers seem to have given their moral support to these deplorable verdicts by affirming that an individual's intelligence is a fixed quantity, a quantity that cannot be increased. We must protest and react against this brutal pessimism; we must try to demonstrate that it is founded on nothing.

The Mismeasure of Man
Some scientists dispute psychometrics entirely. In The Mismeasure of Man professor Stephen Jay Gould argued that intelligence tests were based on faulty assumptions and showed their history of being used as the basis for scientific racism. He wrote:


 * …the abstraction of intelligence as a single entity, its location within the brain, its quantification as one number for each individual, and the use of these numbers to rank people in a single series of worthiness, invariably to find that oppressed and disadvantaged groups—races, classes, or sexes—are innately inferior and deserve their status. (pp. 24–25)

He spent much of the book criticizing the concept of IQ, including a historical discussion of how the IQ tests were created and a technical discussion of why g is simply a mathematical artifact. Later editions of the book included criticism of The Bell Curve.

Gould does not dispute the stability of test scores, nor the fact that they predict certain forms of achievement. He does argue, however, that to base a concept of intelligence on these test scores alone is to ignore many important aspects of mental ability.

Relation between IQ and intelligence
Several other ways of measuring intelligence have been proposed. Daniel Schacter, Daniel Gilbert, and others have moved beyond general intelligence and IQ as the sole means to describe intelligence.

Test bias
The American Psychological Association's report Intelligence: Knowns and Unknowns (1995) states that that IQ tests as predictors of social achievement are not biased against people of African descent since they predict future performance, such as school achievement, similarly to the way they predict future performance for European descent.

However, IQ tests may well be biased when used in other situations. A 2005 study finds some evidence that the WAIS-R is not culture-fair for Mexican Americans. Other recent studies have questioned the culture-fairness of IQ tests when used in South Africa. Standard intelligence tests, such as the Stanford-Binet, are often inappropriate for children with autism; the alternative of using developmental or adaptive skills measures are relatively poor measures of intelligence in autistic children, and have resulted in incorrect claims that a majority of children with autism are mentally retarded.

Outdated Methodology
A 2006 paper argues that mainstream contemporary test analysis does not reflect substantial recent developments in the field and "bears an uncanny resemblance to the psychometric state of the art as it existed in the 1950s." It also claims that some of the most influential recent studies on group differences in intelligence, in order to show that the tests are unbiased, use outdated methodology.

Examples of Intelligence tests

 * Kids IQ Test Center - Age Appropriate Online IQ Tests for Kids.
 * IQ tests like Mensa
 * Free IQ Test reviews
 * Free IQ Test from the BBC - Note average score of 96 not 100 as standard

Collective statements

 * The Wall Street Journal: Mainstream Science on Intelligence
 * PDF Reprint - Mainstream science on intelligence: An editorial with 52 signatories, history, and bibliography.
 * Scientific American: Intelligence Considered

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