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
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. The third edition of the WAIS
(WAIS-III) is the most widely used psychological test in the world, and the
fourth edition of the WISC (WISC-IV) is the most widely used intelligence test
for children. 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—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-Third Edition). The WAIS-III consists of fourteen subtests, seven verbal
(Information, Comprehension, Arithmetic, Similarities, Vocabulary, Digit Span,
and Letter-Number Sequencing) 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 chart
IQ reference charts are tables, suggested by psychologists to divide
intelligence ranges in various categories.
High IQ societies
High IQ society
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
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 Inheritance of intelligence
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; <ref name="Neisser95" /> 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.<ref name="Plomin0103" />
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..<ref name="Neisser95" />
* 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.<ref name="Neisser95" /> 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.<ref name="Neisser95" />
* 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.
<ref name="Neisser95" />
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).<ref name="Plomin0103" /> The American
Psychological Association's report Intelligence: Knowns and Unknowns (1995)<ref
name="Neisser95" /> 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."<ref name="Neisser95" />
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.<ref name="Stoolmiller99" /> 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 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 genetic heritable adaptation. 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
Mental retardation
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
Neuroscience and intelligence
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
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
Health and intelligence
Persons with a higher IQ have generally lower adult morbidity and mortality.
Post-Traumatic Stress Disorder, severe depression, and schizophrenia are less
prevalent in higher IQ bands.
A study of 11,282 individuals in Scotland who took intelligence tests at ages 7,
9 and 11 in the 1950s and 1960s, found an "inverse linear association" between
childhood IQ scores and hospital admissions for injuries in adulthood. The
association between childhood IQ and the risk of later injury remained even
after accounting for factors such as the child's socioeconomic background.
Research in Scotland has also shown that a 15-point lower IQ meant people had a
fifth less chance of seeing their 76th birthday, while those with a 30-point
disadvantage were 37% less likely than those with a higher IQ to live that long.
A decrease in IQ has also been shown as an early predictor of late-onset
Alzheimer's Disease and other forms of dementia. In a 2004 study, Cervilla and
colleagues showed that tests of cognitive ability provide useful predictive
information up to a decade before the onset of dementia. However, when
diagnosing individuals with a higher level of cognitive ability, in this study
those with IQ's of 120 or more, patients should not be diagnosed from the
standard norm but from an adjusted high-IQ norm that measured changes against
the individual's higher ability level. In 2000, Whalley and colleagues published
a paper in the journal Neurology, which examined links between childhood mental
ability and late-onset dementia. The study showed that mental ability scores
were significantly lower in children who eventually developed late-onset
dementia when compared with other children tested.
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 (Gale, CR.
"IQ in childhood and vegetarianism in adulthood: 1970 British cohort study".
British Journal of Medicine 334 (7587): 245. ), and inversely correlates with
the chances of smoking (Taylor, MD. "Childhood IQ and social factors on smoking
behaviour, lung function and smoking-related outcomes in adulthood: linking the
Scottish Mental Survey 1932 and the Midspan studies". British Journal of Health
Psychology 10 (3): 399-401. ), becoming obese, and having serious traumatic
accidents in adulthood.
Sex and IQ
Sex and intelligence
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
Race and intelligence
Much research has been devoted to the extent and potential causes of racial
group differences in IQ.
Positive correlations with IQ
This article or section may deal primarily with the U.S. and may not present a
worldwide view.
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)<ref name="Neisser95" /> 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)<ref name="Hunter84" /> 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)<ref name="Neisser95" /> 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.<ref name="Neisser95" />
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)<ref name="Neisser95" /> 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.<ref name="Neisser95" />
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.<ref name="Neisser95" />
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
Intelligence and 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.<ref name="Neisser95" />.
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.
Criticism
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)<ref name="Neisser95" /> 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.<ref name="Neisser95"
/>
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.
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