SuggestedSources

This response was generated by ChatGPT (o3) without using external sources.

Want to add more sources or suggest new questions? Contribute on GitHub

How accurate are IQ tests?

Introduction
“IQ” (intelligence quotient) tests are standardized psychometric instruments designed to estimate certain cognitive abilities relative to a reference population. Their “accuracy” can be discussed in two separate but related ways: (a) reliability—how precisely and consistently they measure whatever they measure, and (b) validity—how well that measured construct corresponds to the broader idea of “intelligence” and predicts meaningful outcomes. Below is a concise review of the evidence.

What contemporary IQ tests attempt to measure
• Most modern batteries (e.g., WAIS-IV, WISC-V, Stanford-Binet 5, Woodcock–Johnson IV, Raven’s matrices) are built to quantify general cognitive ability, often called g.
• Subtests tap specific domains—verbal comprehension, working memory, processing speed, fluid reasoning, visual–spatial skills—and are combined into a Full-Scale IQ (FSIQ).
• Scores are norm-referenced: the population mean is set at 100, SD at 15. An individual’s score is therefore relative, not absolute.
Reliability (precision)
Reliability coefficients range from .90 to .97 for the major instruments, which is considered excellent in psychological testing.
• Test–retest reliability: Correlations over short intervals (weeks to a few months) are usually ≥ .90 for FSIQ; over years they attenuate modestly (.70–.85), partly because true ability can change.
• Internal consistency: Split-half or coefficient alpha values are typically .95+.
• Inter-scorer reliability: Because scoring is largely objective, agreement across examiners is ≥ .98 on most subtests.
Standard error of measurement (SEM): Roughly ±3–5 IQ points for FSIQ, meaning a score of 110 reflects a likely “true” range of about 105–115 68 % of the time.
Validity (accuracy in measuring ‘intelligence’)
Construct validity
• Factor-analytic studies repeatedly show that IQ tests load strongly on a single general factor (g), supporting the claim they assess a core cognitive construct rather than an arbitrary collection of tasks.
Criterion and predictive validity
• Academic achievement: IQ correlates ~.50–.70 with standardized school tests and GPA.
• Job performance: Meta-analyses give correlations of .30–.60 between IQ and work performance, varying by job complexity.
• Health, income, longevity, and other life-outcomes show modest correlations (.10–.30).
Content validity
• Tests are designed to tap cognitive skills widely regarded as important (reasoning, memory, processing speed). They do not deliberately measure creativity, practical know-how, social/emotional intelligence, or domain-specific knowledge.
Stability across the lifespan
• Scores are less stable in early childhood but increase in stability after age ~8.
• From late adolescence onward, rank-order stability across decades remains around .70–.80, similar to many medical/laboratory tests.
Sources of error and limitation
a. Sampling error: The SEM limits precision; small fluctuations in motivation, fatigue, illness, or test familiarity can shift scores 5–10 points.
b. Cultural and linguistic bias: Although modern norms strive for representativeness and items are empirically screened, group-level differences (by SES, education quality, culture, and race/ethnicity) persist. Debate continues on how much reflects test bias versus real disparities in underlying skills.
c. Stereotype threat and test anxiety can transiently depress performance for some groups.
d. Restricted definition of intelligence: The construct “g” does not exhaust the ways humans solve problems or adapt.
e. Flynn Effect: Raw scores have risen ~3 points per decade during the 20th century, prompting periodic renorming. Comparisons across cohorts must therefore use contemporaneous norms.
What IQ tests DO predict well
• Performance in formal learning environments.
• Technical or cognitively complex job performance.
• Pace of training and error rates in many occupational settings.
• Risk of certain developmental or neurocognitive disorders when scores are extremely low.
What IQ tests do NOT measure well
• Creativity, divergent thinking, artistic or musical talent.
• Emotional intelligence, social acuity, motivation, persistence.
• Morality, personality traits, and many practical life skills.
• Future success in every domain—correlations are probabilistic, not determinative.
Misinterpretations to avoid
• An IQ score is not a fixed “ceiling.” Interventions (education quality, cognitive training, health improvements) can raise average group scores and, to a lesser extent, individuals’ scores.
• IQ differences between groups do not automatically imply genetic causes; environment plays a substantial role.
• The number (e.g., 115 vs. 120) should be interpreted as a range, not as a precise ranking.

Conclusion
IQ tests are highly reliable and possess substantial, though not perfect, validity for predicting certain academic and occupational outcomes. Their accuracy—within about ±5 points for an individual—is on par with many accepted psychological and educational measures. However, they capture only a subset of human cognitive abilities, are influenced by cultural and situational factors, and should be interpreted probabilistically and in context, ideally alongside other assessments.