⌚ Verbal Fluency Test And Emotional Intelligence

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Verbal Fluency Test And Emotional Intelligence



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DAILY Verbal Fluency Free Association Exercise

Verbal reasoning is understanding concepts framed in words. Verbal reasoning is not about fluency or vocabulary, but aims at evaluating one's ability to think constructively. Verbal reasoning tests provide a fair assessment of an individual's ability to think, reason and solve problems in different ways. For that reason, verbal reasoning tests are often used in school admission tests and recruitment settings.

Practice your verbal reasoning with this test. Use your verbal reasoning skills to answer these questions. In the results you'll see your answers, the correct answers and an explanation. This test measures your ability to draw logical conclusions based on written information. Each question presents one or more paragraphs of text and a question about the information in the text. It's your job to figure out which of the options is the correct answer. Using our tests Tickets for tests. Frequently asked questions About test Team Used and mentioned Contact. JavaScript For full functionality of this site it is necessary to enable JavaScript. Nonverbal or "performance" tests were developed for those who could not speak English or were suspected of malingering.

At the start of the war, the army and national guard maintained nine thousand officers. By the end, two hundred thousand officers presided, and two- thirds of them had started their careers in training camps where the tests were applied. In some camps, no man scoring below C could be considered for officer training. The results of these tests, which at the time reaffirmed contemporary racism and nationalism, are considered controversial and dubious, having rested on certain contested assumptions: that intelligence was heritable, innate, and could be relegated to a single number, the tests were enacted systematically, and test questions actually tested for innate intelligence rather than subsuming environmental factors.

Thurstone argued for a model of intelligence that included seven unrelated factors verbal comprehension, word fluency, number facility, spatial visualization, associative memory, perceptual speed, reasoning, and induction. While not widely used, Thurstone's model influenced later theories. David Wechsler produced the first version of his test in It gradually became more popular and overtook the Stanford-Binet in the s. It has been revised several times, as is common for IQ tests, to incorporate new research. One explanation is that psychologists and educators wanted more information than the single score from the Binet.

Wechsler's ten or more subtests provided this. Another is that the Stanford-Binet test reflected mostly verbal abilities, while the Wechsler test also reflected nonverbal abilities. The Stanford-Binet has also been revised several times and is now similar to the Wechsler in several aspects, but the Wechsler continues to be the most popular test in the United States.

Eugenics , a set of beliefs and practices aimed at improving the genetic quality of the human population by excluding people and groups judged to be inferior and promoting those judged to be superior, [39] [40] [41] played a significant role in the history and culture of the United States during the Progressive Era , from the late 19th century until US involvement in World War II. The American eugenics movement was rooted in the biological determinist ideas of the British Scientist Sir Francis Galton. In , Galton first used the word eugenics to describe the biological improvement of human genes and the concept of being "well-born". Goddard was a eugenicist. In , he published his own version, The Binet and Simon Test of Intellectual Capacity , and cordially promoted the test.

He quickly extended the use of the scale to the public schools , to immigration Ellis Island , and to a court of law Unlike Galton, who promoted eugenics through selective breeding for positive traits, Goddard went with the US eugenics movement to eliminate "undesirable" traits. He argued that "feeble-mindedness" was caused by heredity, and thus feeble-minded people should be prevented from giving birth, either by institutional isolation or sterilization surgeries. Goddard's intelligence test was endorsed by the eugenicists to push for laws for forced sterilization.

Different states adopted the sterilization laws at different paces. These laws, whose constitutionality was upheld by the Supreme Court in their ruling Buck v. Bell , forced over 64, people to go through sterilization in the United States. California's sterilization program was so effective that the Nazis turned to the government for advice on how to prevent the birth of the "unfit".

Raymond Cattell proposed two types of cognitive abilities in a revision of Spearman's concept of general intelligence. Fluid intelligence Gf was hypothesized as the ability to solve novel problems by using reasoning, and crystallized intelligence Gc was hypothesized as a knowledge-based ability that was very dependent on education and experience. In addition, fluid intelligence was hypothesized to decline with age, while crystallized intelligence was largely resistant to the effects of aging.

The theory was almost forgotten, but was revived by his student John L. Horn who later argued Gf and Gc were only two among several factors, and who eventually identified nine or ten broad abilities. The theory continued to be called Gf-Gc theory. John B. Carroll , after a comprehensive reanalysis of earlier data, proposed the three stratum theory , which is a hierarchical model with three levels. The bottom stratum consists of narrow abilities that are highly specialized e. The second stratum consists of broad abilities. Carroll identified eight second-stratum abilities. Carroll accepted Spearman's concept of general intelligence, for the most part, as a representation of the uppermost, third stratum.

In , a merging of the Gf-Gc theory of Cattell and Horn with Carroll's Three-Stratum theory has led to the Cattell—Horn—Carroll theory CHC Theory , with g as the top of the hierarchy, ten broad abilities below, and further subdivided into seventy narrow abilities on the third stratum. Modern tests do not necessarily measure all of these broad abilities. More recent research has shown the situation to be more complex. Although they still give an overall score, they now also give scores for many of these more restricted abilities, identifying particular strengths and weaknesses of an individual. An alternative to standard IQ tests, meant to test the proximal development of children, originated in the writings of psychologist Lev Vygotsky — during his last two years of his life.

The difference between this level of potential and the lower level of unassisted performance indicates the child's zone of proximal development. Dynamic assessment has been further elaborated in the work of Ann Brown , and John D. Bransford and in theories of multiple intelligences authored by Howard Gardner and Robert Sternberg. Guilford 's Structure of Intellect model of intelligence used three dimensions, which, when combined, yielded a total of types of intelligence. It was popular in the s and early s, but faded owing to both practical problems and theoretical criticisms. It argued that only looking at one general factor was inadequate for researchers and clinicians who worked with learning disabilities, attention disorders, intellectual disability, and interventions for such disabilities.

The planning processes involve decision making, problem solving, and performing activities and require goal setting and self-monitoring. Simultaneous processing involves the integration of stimuli into a group and requires the observation of relationships. Successive processing involves the integration of stimuli into serial order. There are a variety of individually administered IQ tests in use in the English-speaking world.

IQ scales are ordinally scaled. In particular, IQ points are not percentage points. Psychometricians generally regard IQ tests as having high statistical reliability. Like all statistical quantities, any particular estimate of IQ has an associated standard error that measures uncertainty about the estimate. For modern tests, the confidence interval can be approximately 10 points and reported standard error of measurement can be as low as about three points. Outside influences such as low motivation or high anxiety can occasionally lower a person's IQ test score. Reliability and validity are very different concepts. While reliability reflects reproducibility, validity refers to lack of bias.

A biased test does not measure what it purports to measure. For this reason, psychologist Wayne Weiten argues that their construct validity must be carefully qualified, and not be overstated. But if the purpose is to assess intelligence in a broader sense, the validity of IQ tests is questionable. Some scientists have disputed the value of IQ as a measure of intelligence altogether.

Along these same lines, critics such as Keith Stanovich do not dispute the capacity of IQ test scores to predict some kinds of achievement, but argue that basing a concept of intelligence on IQ test scores alone neglects other important aspects of mental ability. Despite these objections, clinical psychologists generally regard IQ scores as having sufficient statistical validity for many clinical purposes. Differential item functioning DIF , sometimes referred to as measurement bias, is a phenomenon when participants from different groups e.

A consistent different group response to a specific question among similar types of questions can indicate an effect of DIF. It does not count as differential item functioning if both groups have an equally valid chance of giving different responses to the same questions. Such bias can be a result of culture, educational level and other factors that are independent of group traits. DIF is only considered if test-takers from different groups with the same underlying latent ability level have a different chance of giving specific responses.

A study found that "differential validity in prediction suggests that the WAIS-R test may contain cultural influences that reduce the validity of the WAIS-R as a measure of cognitive ability for Mexican American students," [98] indicating a weaker positive correlation relative to sampled white students. Other recent studies have questioned the culture-fairness of IQ tests when used in South Africa. Since the early 20th century, raw scores on IQ tests have increased in most parts of the world. The phenomenon of rising raw score performance means if test-takers are scored by a constant standard scoring rule, IQ test scores have been rising at an average rate of around three IQ points per decade. Flynn , the author who did the most to bring this phenomenon to the attention of psychologists.

Researchers have been exploring the issue of whether the Flynn effect is equally strong on performance of all kinds of IQ test items, whether the effect may have ended in some developed nations, whether there are social subgroup differences in the effect, and what possible causes of the effect might be. Mackintosh , noted the Flynn effect demolishes the fears that IQ would be decreased. He also asks whether it represents a real increase in intelligence beyond IQ scores.

Research has revealed that the Flynn effect has slowed or reversed course in several Western countries beginning in the late 20th century. The phenomenon has been termed the negative Flynn effect. IQ can change to some degree over the course of childhood. For decades, practitioners' handbooks and textbooks on IQ testing have reported IQ declines with age after the beginning of adulthood. However, later researchers pointed out this phenomenon is related to the Flynn effect and is in part a cohort effect rather than a true aging effect.

A variety of studies of IQ and aging have been conducted since the norming of the first Wechsler Intelligence Scale drew attention to IQ differences in different age groups of adults. The current consensus is that fluid intelligence generally declines with age after early adulthood, while crystallized intelligence remains intact. Both cohort effects the birth year of the test-takers and practice effects test-takers taking the same form of IQ test more than once must be controlled to gain accurate data. The exact peak age of fluid intelligence or crystallized intelligence remains elusive. Cross-sectional studies usually show that especially fluid intelligence peaks at a relatively young age often in the early adulthood while longitudinal data mostly show that intelligence is stable until mid-adulthood or later.

Subsequently, intelligence seems to decline slowly. Environmental and genetic factors play a role in determining IQ. Their relative importance has been the subject of much research and debate. The general figure for the heritability of IQ, according to an authoritative American Psychological Association report, is 0. Family members have aspects of environments in common for example, characteristics of the home. This shared family environment accounts for 0. By late adolescence, it is quite low zero in some studies. The effect for several other psychological traits is similar. These studies have not looked at the effects of extreme environments, such as in abusive families. Although parents treat their children differently, such differential treatment explains only a small amount of nonshared environmental influence.

One suggestion is that children react differently to the same environment because of different genes. More likely influences may be the impact of peers and other experiences outside the family. A very large proportion of the over 17, human genes are thought to have an effect on the development and functionality of the brain. Deary and colleagues reported that no finding of a strong single gene effect on IQ has been replicated. David Rowe reported an interaction of genetic effects with socioeconomic status , such that the heritability was high in high-SES families, but much lower in low-SES families. Dickens and Flynn have argued that genes for high IQ initiate an environment-shaping feedback cycle , with genetic effects causing bright children to seek out more stimulating environments that then further increase their IQ.

In Dickens' model, environment effects are modeled as decaying over time. In this model, the Flynn effect can be explained by an increase in environmental stimulation independent of it being sought out by individuals. The authors suggest that programs aiming to increase IQ would be most likely to produce long-term IQ gains if they enduringly raised children's drive to seek out cognitively demanding experiences. In general, educational interventions, as those described below, have shown short-term effects on IQ, but long-term follow-up is often missing.

Even when students improve their scores on standardized tests, they do not always improve their cognitive abilities, such as memory, attention and speed. Recent studies have shown that training in using one's working memory may increase IQ. A study on young adults published in April by a team from the Universities of Michigan and Bern supports the possibility of the transfer of fluid intelligence from specifically designed working memory training. Among other questions, it remains to be seen whether the results extend to other kinds of fluid intelligence tests than the matrix test used in the study, and if so, whether, after training, fluid intelligence measures retain their correlation with educational and occupational achievement or if the value of fluid intelligence for predicting performance on other tasks changes.

It is also unclear whether the training is durable for extended periods of time. Musical training in childhood correlates with higher than average IQ. It is popularly thought that listening to classical music raises IQ. However, multiple attempted replications e. Several neurophysiological factors have been correlated with intelligence in humans, including the ratio of brain weight to body weight and the size, shape, and activity level of different parts of the brain. Specific features that may affect IQ include the size and shape of the frontal lobes, the amount of blood and chemical activity in the frontal lobes, the total amount of gray matter in the brain, the overall thickness of the cortex, and the glucose metabolic rate.

Health is important in understanding differences in IQ test scores and other measures of cognitive ability. 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 sometimes be partially or wholly compensated for by later growth. Since about , researchers such as Eppig, Hassel, and MacKenzie have found a very close and consistent link between IQ scores and infectious diseases, especially in the infant and preschool populations and the mothers of these children. Hassel postulated that it is by far the most important factor in determining population IQ.

However, they also found that subsequent factors such as good nutrition and regular quality schooling can offset early negative effects to some extent. 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.

Improvements in nutrition, and in public policy in general, have been implicated in worldwide IQ increases. Cognitive epidemiology is a field of research that examines the associations between intelligence test scores and health. Researchers in the field argue that intelligence measured at an early age is an important predictor of later health and mortality differences.

The American Psychological Association 's report Intelligence: Knowns and Unknowns states that 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. Achieving good grades depends on many factors other than IQ, such as "persistence, interest in school, and willingness to study" p. It has been found that the correlation of IQ scores with school performance depends on the IQ measurement used. 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.

In establishing a causal direction to the link between IQ and work performance, longitudinal studies by Watkins and others suggest that IQ exerts a causal influence on future academic achievement, whereas academic achievement does not substantially influence future IQ scores. The US military has minimum enlistment standards at about the IQ 85 level. There have been two experiments with lowering this to 80 but in both cases these men could not master soldiering well enough to justify their costs.

It has been suggested that "in economic terms it appears that the IQ score measures something with decreasing marginal value" and it "is important to have enough of it, but having lots and lots does not buy you that much". The link from IQ to wealth is much less strong than that from IQ to job performance. Some studies indicate that IQ is unrelated to net worth.

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. Some studies assert that IQ only accounts for explains a sixth of the variation in income because many studies are based on young adults, many of whom have not yet reached their peak earning capacity, or even their education. On pg of The g Factor , Arthur Jensen says that although the correlation between IQ and income averages a moderate 0.

A study [] further examined the impact of non-IQ factors on income and concluded that an individual's location, inherited wealth, race, and schooling are more important as factors in determining income than IQ. This association is generally regarded as small and prone to disappear or be substantially reduced after controlling for the proper covariates, being much smaller than typical sociological correlates.

A correlation of 0. The causal links between psychometric ability and social outcomes may be indirect. Children with poor scholastic performance may feel alienated. Consequently, they may be more likely to engage in delinquent behavior, compared to other children who do well. In his book The g Factor , Arthur Jensen cited data which showed that, regardless of race, people with IQs between 70 and 90 have higher crime rates than people with IQs below or above this range, with the peak range being between 80 and The Handbook of Crime Correlates stated that reviews have found that around eight IQ points, or 0.

It has been suggested that this simply reflects that "only dumb ones get caught" but there is similarly a negative relation between IQ and self-reported offending. That children with conduct disorder have lower IQ than their peers "strongly argues" for the theory. A study of the relationship between US county-level IQ and US county-level crime rates found that higher average IQs were very weakly associated with lower levels of property crime, burglary, larceny rate, motor vehicle theft, violent crime, robbery, and aggravated assault.

These results were "not confounded by a measure of concentrated disadvantage that captures the effects of race, poverty, and other social disadvantages of the county. It has also been shown that the effect of IQ is heavily dependent on socioeconomic status and that it cannot be easily controlled away, with many methodological considerations being at play. Multiple studies conducted in Scotland have found that higher IQs in early life are associated with lower mortality and morbidity rates later in life. There is considerable variation within and overlap among these categories. People with high IQs are found at all levels of education and occupational categories.

The biggest difference occurs for low IQs with only an occasional college graduate or professional scoring below Among the most controversial issues related to the study of intelligence is the observation that intelligence measures such as IQ scores vary between ethnic and racial groups. While there is little scholarly debate about the existence of some of these differences, current scientific consensus tells us that there is no evidence for a genetic component behind them. With the advent of the concept of g or general intelligence , many researchers have argued that there are no significant sex differences in general intelligence, [] [] [] though ability in particular types of intelligence does appear to vary.

Some research indicates that male advantages on some cognitive tests are minimized when controlling for socioeconomic factors. The existence of differences between male and female performance on math-related tests is contested, [] and a meta-analysis focusing on gender differences in math performance found nearly identical performance for boys and girls. While the concept of " race " is a social construct , [] discussions of a purported relationship between race and intelligence, as well as claims of genetic differences in intelligence along racial lines, have appeared in both popular science and academic research since the modern concept of race was first introduced.

Despite the tremendous amount of research done on the topic, no scientific evidence has emerged that the average IQ scores of different population groups can be attributed to genetic differences between those groups. A task force investigation on intelligence sponsored by the American Psychological Association concluded that there were significant variations in IQ across races. The problem of determining the causes underlying racial variation has been discussed at length as a classic question of " nature versus nurture ", for instance by Alan S.

Kaufman [] and Nathan Brody. The effects of stereotype threat have been proposed as an explanation for differences in IQ test performance between racial groups, [] [] as have issues related to cultural difference and access to education. In the United States, certain public policies and laws regarding military service, [] [] education, public benefits, [] capital punishment, [] and employment incorporate an individual's IQ into their decisions.

However, in the case of Griggs v. Duke Power Co. Supreme Court banned the use of IQ tests in employment, except when linked to job performance via a job analysis. Internationally, certain public policies, such as improving nutrition and prohibiting neurotoxins , have as one of their goals raising, or preventing a decline in, intelligence. A diagnosis of intellectual disability is in part based on the results of IQ testing.

Borderline intellectual functioning is a categorization where a person has below-average cognitive ability an IQ of 71—85 , but the deficit is not as severe as intellectual disability 70 or below. In the United Kingdom, the eleven plus exam which incorporated an intelligence test has been used from to decide, at eleven years of age, which type of school a child should go to. They have been much less used since the widespread introduction of comprehensive schools. IQ classification is the practice used by IQ test publishers for designating IQ score ranges into various categories with labels such as "superior" or "average. Those other forms of behavioral observation are still important for validating classifications based on IQ tests.

There are social organizations, some international, which limit membership to people who have scores as high as or higher than the 98th percentile 2 standard deviations above the mean on some IQ test or equivalent. Mensa International is perhaps the best known of these. The largest From Wikipedia, the free encyclopedia. This is the latest accepted revision , reviewed on 29 September Score derived from tests purported to measure individual differences in human intelligence.

For other uses, see IQ disambiguation. Basic types. Applied psychology. See also: History of the race and intelligence controversy. Main article: g factor. Main article: Cattell—Horn—Carroll theory. Main article: Flynn effect. See also: Heritability of IQ and Environment and intelligence. Main article: Neuroscience and intelligence. This section needs additional citations for verification. Please help improve this article by adding citations to reliable sources. Unsourced material may be challenged and removed. Main articles: Impact of health on intelligence and Cognitive epidemiology. Main article: Sex differences in intelligence.

Main article: Race and intelligence. Main article: Intelligence and public policy. Main article: IQ classification. This is known as Spearman's two-factor theory. Later research based on more diverse test batteries than those used by Spearman demonstrated that g alone could not account for all correlations between tests. Specifically, it was found that even after controlling for g , some tests were still correlated with each other. This led to the postulation of group factors that represent variance that groups of tests with similar task demands e. Through factor rotation , it is, in principle, possible to produce an infinite number of different factor solutions that are mathematically equivalent in their ability to account for the intercorrelations among cognitive tests.

These include solutions that do not contain a g factor. Thus factor analysis alone cannot establish what the underlying structure of intelligence is. In choosing between different factor solutions, researchers have to examine the results of factor analysis together with other information about the structure of cognitive abilities. There are many psychologically relevant reasons for preferring factor solutions that contain a g factor. These include the existence of the positive manifold, the fact that certain kinds of tests generally the more complex ones have consistently larger g loadings, the substantial invariance of g factors across different test batteries, the impossibility of constructing test batteries that do not yield a g factor, and the widespread practical validity of g as a predictor of individual outcomes.

The g factor, together with group factors, best represents the empirically established fact that, on average, overall ability differences between individuals are greater than differences among abilities within individuals, while a factor solution with orthogonal factors without g obscures this fact. Moreover, g appears to be the most heritable component of intelligence. A g factor can be computed from a correlation matrix of test results using several different methods. These include exploratory factor analysis, principal components analysis PCA , and confirmatory factor analysis.

Different factor-extraction methods produce highly consistent results, although PCA has sometimes been found to produce inflated estimates of the influence of g on test scores. There is a broad contemporary consensus that cognitive variance between people can be conceptualized at three hierarchical levels, distinguished by their degree of generality. At the lowest, least general level there are many narrow first-order factors; at a higher level, there are a relatively small number — somewhere between five and ten — of broad i.

Spearman proposed the principle of the indifference of the indicator , according to which the precise content of intelligence tests is unimportant for the purposes of identifying g , because g enters into performance on all kinds of tests. Any test can therefore be used as an indicator of g. Thus a composite score of a number of different tests will load onto g more strongly than any of the individual test scores, because the g components cumulate into the composite score, while the uncorrelated non- g components will cancel each other out. Theoretically, the composite score of an infinitely large, diverse test battery would, then, be a perfect measure of g.

In contrast, L. Thurstone argued that a g factor extracted from a test battery reflects the average of all the abilities called for by the particular battery, and that g therefore varies from one battery to another and "has no fundamental psychological significance. To show that different batteries reflect the same g , one must administer several test batteries to the same individuals, extract g factors from each battery, and show that the factors are highly correlated. This can be done within a confirmatory factor analysis framework. The second study found that g factors derived from four of five test batteries correlated at between. They attributed the somewhat lower correlations with the CFIT battery to its lack of content diversity for it contains only matrix-type items, and interpreted the findings as supporting the contention that g factors derived from different test batteries are the same provided that the batteries are diverse enough.

The results suggest that the same g can be consistently identified from different test batteries. The form of the population distribution of g is unknown, because g cannot be measured on a ratio scale [ clarification needed ]. The distributions of scores on typical IQ tests are roughly normal, but this is achieved by construction, i. It has been argued [ who? In particular, g can be thought of as a composite variable that reflects the additive effects of many independent genetic and environmental influences, and such a variable should, according to the central limit theorem , follow a normal distribution.

A number of researchers have suggested that the proportion of variation accounted for by g may not be uniform across all subgroups within a population. Spearman's law of diminishing returns SLODR , also termed the cognitive ability differentiation hypothesis , predicts that the positive correlations among different cognitive abilities are weaker among more intelligent subgroups of individuals. More specifically, SLODR predicts that the g factor will account for a smaller proportion of individual differences in cognitive tests scores at higher scores on the g factor.

SLODR was originally proposed by Charles Spearman , [54] who reported that the average correlation between 12 cognitive ability tests was. Detterman and Daniel rediscovered this phenomenon in SLODR has been replicated in a variety of child and adult samples who have been measured using broad arrays of cognitive tests. The most common approach has been to divide individuals into multiple ability groups using an observable proxy for their general intellectual ability, and then to either compare the average interrelation among the subtests across the different groups, or to compare the proportion of variation accounted for by a single common factor, in the different groups.

Tucker-Drob [58] extensively reviewed the literature on SLODR and the various methods by which it had been previously tested, and proposed that SLODR could be most appropriately captured by fitting a common factor model that allows the relations between the factor and its indicators to be nonlinear in nature. He applied such a factor model to a nationally representative data of children and adults in the United States and found consistent evidence for SLODR.

A recent meta-analytic study by Blum and Holling [59] also provided support for the differentiation hypothesis. As opposed to most research on the topic, this work made it possible to study ability and age variables as continuous predictors of the g saturation, and not just to compare lower- vs. Results demonstrate that the mean correlation and g loadings of cognitive ability tests decrease with increasing ability, yet increase with respondent age.

SLODR , as described by Charles Spearman , could be confirmed by a g -saturation decrease as a function of IQ as well as a g -saturation increase from middle age to senescence. Specifically speaking, for samples with a mean intelligence that is two standard deviations i. The question remains whether a difference of this magnitude could result in a greater apparent factorial complexity when cognitive data are factored for the higher-ability sample, as opposed to the lower-ability sample. It seems likely that greater factor dimensionality should tend to be observed for the case of higher ability, but the magnitude of this effect i. The practical validity of g as a predictor of educational, economic, and social outcomes is the subject of ongoing debate.

A test's practical validity is measured by its correlation with performance on some criterion external to the test, such as college grade-point average, or a rating of job performance. The correlation between test scores and a measure of some criterion is called the validity coefficient. One way to interpret a validity coefficient is to square it to obtain the variance accounted by the test. For example, a validity coefficient of. This approach has, however, been criticized as misleading and uninformative, and several alternatives have been proposed. One arguably more interpretable approach is to look at the percentage of test takers in each test score quintile who meet some agreed-upon standard of success. For example, if the correlation between test scores and performance is.

The predictive validity of g is most conspicuous in the domain of scholastic performance. This is apparently because g is closely linked to the ability to learn novel material and understand concepts and meanings. In elementary school, the correlation between IQ and grades and achievement scores is between. At more advanced educational levels, more students from the lower end of the IQ distribution drop out, which restricts the range of IQs and results in lower validity coefficients. In high school, college, and graduate school the validity coefficients are. The g loadings of IQ scores are high, but it is possible that some of the validity of IQ in predicting scholastic achievement is attributable to factors measured by IQ independent of g.

According to research by Robert L. Thorndike , 80 to 90 percent of the predictable variance in scholastic performance is due to g , with the rest attributed to non- g factors measured by IQ and other tests. Achievement test scores are more highly correlated with IQ than school grades. This may be because grades are more influenced by the teacher's idiosyncratic perceptions of the student. The correlations ranged from. The correlation between g and a general educational factor computed from the GCSE tests was. Research suggests that the SAT , widely used in college admissions, is primarily a measure of g.

A correlation of. In a study of , students at 41 U. There is a high correlation of. At the level of individual employees, the association between job prestige and g is lower — one large U. Mean level of g thus increases with perceived job prestige. It has also been found that the dispersion of general intelligence scores is smaller in more prestigious occupations than in lower level occupations, suggesting that higher level occupations have minimum g requirements.

Research indicates that tests of g are the best single predictors of job performance, with an average validity coefficient of. The average meta-analytic validity coefficient for performance in job training is. Research also shows that specific aptitude tests tailored for each job provide little or no increase in predictive validity over tests of general intelligence. It is believed that g affects job performance mainly by facilitating the acquisition of job-related knowledge.

The predictive validity of g is greater than that of work experience, and increased experience on the job does not decrease the validity of g. In a meta-analysis, researchers found that general cognitive ability GCA predicted job performance better than personality Five factor model and three streams of emotional intelligence. They examined the relative importance of these constructs on predicting job performance and found that cognitive ability explained most of the variance in job performance. Although these compensatory effects favour emotional intelligence , GCA still remains as the best predictor of job performance. Several researchers have studied the correlation between GCA and job performance among different job positions. For instance, Ghiselli [78] found that salespersons had a higher correlation than sales clerk.

The former obtained a correlation of 0. Hunter and Hunter [80] developed a meta-analysis with over studies and found that this correlation was higher for jobs of high complexity 0. Followed by jobs of medium complexity 0. Job performance is measured by objective rating performance and subjective ratings. Although the former is better than subjective ratings, most of studies in job performance and GCA have been based on supervisor performance ratings. This rating criteria is considered problematic and unreliable, mainly because of its difficulty to define what is a good and bad performance.

Rating of supervisors tends to be subjective and inconsistent among employees. These findings were surprising, considering that the main criteria for assessing these employees would be the objective sales. In understanding how GCA is associated job performance, several researchers concluded that GCA affects acquisition of job knowledge, which in turn improves job performance. In other words, people high in GCA are capable to learn faster and acquire more job knowledge easily, which allow them to perform better. Conversely, lack of ability to acquire job knowledge will directly affect job performance.

This is due to low levels of GCA. Also, GCA has a direct effect on job performance. In a daily basis, employees are exposed constantly to challenges and problem solving tasks, which success depends solely on their GCA. These findings are discouraging for governmental entities in charge of protecting rights of workers. Inevitably, this practice is denying the opportunity to work to many people with low GCA. For instance, there is a debate whether studies were biased against Afro-Americans, who scored significantly lower than white Americans in GCA tests. Some researchers have warned the existence of statistical artifacts related to measures of job performance and GCA test scores. For example, Viswesvaran, Ones and Schmidt [88] argued that is quite impossible to obtain perfect measures of job performance without incurring in any methodological error.

Moreover, studies on GCA and job performance are always susceptible to range restriction, because data is gathered mostly from current employees, neglecting those that were not hired. Hence, sample comes from employees who successfully passed hiring process, including measures of GCA. The correlation between income and g , as measured by IQ scores, averages about. The correlation is higher at higher levels of education and it increases with age, stabilizing when people reach their highest career potential in middle age.

Even when education, occupation and socioeconomic background are held constant, the correlation does not vanish. The g factor is reflected in many social outcomes. Many social behavior problems, such as dropping out of school, chronic welfare dependency, accident proneness, and crime, are negatively correlated with g independent of social class of origin. In , psychologist Satoshi Kanazawa argued that g was a domain-specific , species-typical , information processing psychological adaptation , [93] and in , Kanazawa argued that g correlated only with performance on evolutionarily unfamiliar rather than evolutionarily familiar problems, proposing what he termed the "Savanna-IQ interaction hypothesis".

Gray published a study in in Intelligence of subjects taking a item computer version of the Wason selection task a logic puzzle in a social relations context as proposed by evolutionary psychologists Leda Cosmides and John Tooby in The Adapted Mind , [97] and found instead that "performance on non-arbitrary, evolutionarily familiar problems is more strongly related to general intelligence than performance on arbitrary, evolutionarily novel problems". Heritability is the proportion of phenotypic variance in a trait in a population that can be attributed to genetic factors.

The heritability of g has been estimated to fall between 40 and 80 percent using twin, adoption, and other family study designs as well as molecular genetic methods. For example, a large study involving more than 11, pairs of twins from four countries reported the heritability of g to be 41 percent at age nine, 55 percent at age twelve, and 66 percent at age seventeen. Other studies have estimated that the heritability is as high as 80 percent in adulthood, although it may decline in old age. Most of the research on the heritability of g has been conducted in the United States and Western Europe , but studies in Russia Moscow , the former East Germany , Japan, and rural India have yielded similar estimates of heritability as Western studies.

Behavioral genetic research has also established that the shared or between-family environmental effects on g are strong in childhood, but decline thereafter and are negligible in adulthood. This indicates that the environmental effects that are important to the development of g are unique and not shared between members of the same family. The genetic correlation is a statistic that indicates the extent to which the same genetic effects influence two different traits. If the genetic correlation between two traits is zero, the genetic effects on them are independent, whereas a correlation of 1. Genetic correlations between specific mental abilities such as verbal ability and spatial ability have been consistently found to be very high, close to 1.

This indicates that genetic variation in cognitive abilities is almost entirely due to genetic variation in whatever g is. It also suggests that what is common among cognitive abilities is largely caused by genes, and that independence among abilities is largely due to environmental effects. Thus it has been argued that when genes for intelligence are identified, they will be "generalist genes", each affecting many different cognitive abilities. Much research points to g being a highly polygenic trait influenced by many common genetic variants, each having only small effects. Another possibility is that heritable differences in g are due to individuals having different "loads" of rare, deleterious mutations, with genetic variation among individuals persisting due to mutation—selection balance.

A number of candidate genes have been reported to be associated with intelligence differences, but the effect sizes have been small and almost none of the findings have been replicated. No individual genetic variants have been conclusively linked to intelligence in the normal range so far. Many researchers believe that very large samples will be needed to reliably detect individual genetic polymorphisms associated with g. It has been suggested that the g loading of mental tests have been found to correlate with heritability, [33] but both the empirical data and statistical methodology bearing on this question are matters of active controversy.

MRI research on brain regions indicates that the volumes of frontal , parietal and temporal cortices , and the hippocampus are also correlated with g , generally at. Some but not all studies have also found positive correlations between g and cortical thickness. However, the underlying reasons for these associations between the quantity of brain tissue and differences in cognitive abilities remain largely unknown.

Most researchers believe that intelligence cannot be localized to a single brain region, such as the frontal lobe. Brain lesion studies have found small but consistent associations indicating that people with more white matter lesions tend to have lower cognitive ability. Research utilizing NMR spectroscopy has discovered somewhat inconsistent but generally positive correlations between intelligence and white matter integrity, supporting the notion that white matter is important for intelligence.

Some research suggests that aside from the integrity of white matter, also its organizational efficiency is related to intelligence. The hypothesis that brain efficiency has a role in intelligence is supported by functional MRI research showing that more intelligent people generally process information more efficiently, i. Small but relatively consistent associations with intelligence test scores include also brain activity, as measured by EEG records or event-related potentials , and nerve conduction velocity. Evidence of a general factor of intelligence has also been observed in non-human animals. While not able to be assessed using the same intelligence measures used in humans, cognitive ability can be measured with a variety of interactive and observational tools focusing on innovation , habit reversal, social learning , and responses to novelty.

Non-human models of g such as mice are used to study genetic influences on intelligence and neurological developmental research into the mechanisms behind and biological correlates of g. Similar to g for individuals, a new research path aims to extract a general collective intelligence factor c for groups displaying a group's general ability to perform a wide range of tasks.

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