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Intelligence quotient

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IQ, an abbreviation for "intelligence quotient", is a score derived from a set of standardized tests and is believed to measure general cognitive ability. It is expressed as a number normalized so that the average IQ in an age group is 100 -- in other words an individual scoring 115 is above-average when compared to similarly aged people. The distribution of IQ scores is more-or-less Gaussian, that is to say that it follows the bell curve.

Modern ability tests produce scores for different areas (e.g. language fluency, three-dimensional thinking, ...), with the summary score being the most meaningless. It is much more useful to know which are the strengths and weaknesses of a person than to know that he or she beats n percent of the populace in some "general intelligence" measure. Two persons with vastly different ability profiles may score the same IQ, but may exhibit different affinity to a given task, or may not be valued equally intelligent by other people.

IQ scores are sometimes taken as an objective measure of intelligence, and since intelligence is notoriously difficult to define, the definition "Intelligence is what the IQ test measures" has been seriously proposed. However, IQ tests encode their creators beliefs about what constitutes intelligence. What various cultures dub "intelligence" differs. Most people also think that creativity plays a significant role in intelligence; creativity is almost unmeasurable by tests.

It is worth noting that Binet, who created the IQ test in 1904, was aiming to identify students who could benefit from extra help in school: his assumption was that lower IQ indicated the need for more teaching, not an inability to learn.

(The following numbers apply to IQ scales with a standard deviation σ=15.) Scores between 90 and 110 are considered average -- so a person scoring 95 is simply average, not below-average. For children scoring below 80 special schooling is encouraged, children above 125 are "highly gifted". IQ scores outside the range 55 to 145 are essentially meaningless because there are not enough people to make statistically sound statements.

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