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How accurate are IQ tests?

When psychologists talk about how “accurate” an IQ test is, they are usually referring to two related but distinct qualities:

  1. Reliability – How consistently the test measures whatever it measures.
  2. Validity – Whether the score really reflects general cognitive ability (the g factor) and predicts real-world outcomes.

Below is what the empirical literature says about each aspect, followed by common limitations and caveats.

  1. Reliability: How consistent are the scores? • Modern, well-normed IQ batteries such as the WAIS-IV, WISC-V and Stanford-Binet-5 show test-retest and split-half reliabilities around .90–.95 for the Full-Scale IQ; most sub-tests are in the .80s [2].
    • A reliability of .90 implies that only about 10 % of the score variance is random measurement error. For an individual, the standard error of measurement is roughly ±3 points, so a person who scores 110 would fall between about 107 and 113 if retested under similar conditions.
    • These reliabilities are considerably higher than those of most psychological scales (e.g., personality inventories typically sit in the .70s) [2].

  2. Validity: Do IQ scores mean anything outside the test room? a) Construct validity
    • Scores from different IQ tests correlate around .80 with one another and load strongly on the same underlying g factor extracted with factor analysis [2][4].
    b) Predictive validity
    • School achievement: r ≈ .50 with GPA and standardized achievement tests, and higher (≈ .70) with years of education completed when socioeconomic status is controlled [2][3].
    • Job performance: meta-analyses put the correlation around .50 for complex jobs, .40 for medium-complexity jobs, and roughly .30 for the simplest jobs [1][2].
    • Training success: correlations are often in the .60s.
    • Long-term life outcomes: IQ at age 11 correlates ≈ .35 with adult income, ≈ –.20 with risk of incarceration, and ≈ .20 with longevity; it also predicts health-related behaviors [2].
    • Cross-group validity: Within-group correlations (e.g., within Black Americans or within women) are the same size as within the full sample, indicating the tests predict equally well across demographic groups even when average scores differ [3][4].

  3. What IQ tests do not do • They are not designed to measure creativity, wisdom, motivation, conscientiousness, or domain-specific knowledge. Those attributes add incremental predictive power beyond IQ.
    • A single score does not capture the pattern of a person’s cognitive strengths and weaknesses.
    • IQ is not fixed at birth. Heritability rises with age, but interventions such as education, nutrition, the elimination of lead exposure, and training on domain skills can still move the mean of a population (e.g., the “Flynn effect”) [2][4].

  4. Common sources of misinterpretation • “Cultural bias”: Some items require knowledge more common in certain cultures, yet the overall predictive validity for academic and occupational outcomes remains similar across groups, implying that most of the variance captured is genuinely cognitive rather than cultural [1][3].
    • Media coverage often cherry-picks extreme or outdated claims, leading laypeople to believe that IQ tests are far less accurate than the data show [3][4].
    • Differences in mean group scores are sometimes confused with test inaccuracy; in fact, group means can differ even when the test is equally accurate for each individual [1].

  5. Bottom line Within the limits of any psychological measurement, IQ tests are among the most reliable tools in the social sciences and possess substantial validity for predicting educational, occupational, and many life outcomes. Accuracy, however, is not perfection: an individual score has a confidence band of several points, IQ leaves a large fraction of variance in life outcomes unexplained, and it tells us nothing about moral worth or potential in domains not strongly tied to g.

Sources
[1] “Breaking the Taboo,” Riot IQ – argues that IQ tests are “one of the most reliable instruments in psychology” (reliability ≈ .90) and retain predictive validity for education and work. https://www.riotiq.com/articles/breaking-the-taboo
[2] S. Stewart-Williams, “12 Things Everyone Should Know About IQ,” The Nature-Nurture-Nietzsche Newsletter – summarizes mainstream findings: high reliability, strong predictive validity, but IQ is not the sole determinant of success or fixed at birth. https://www.stevestewartwilliams.com/p/12-things-everyone-should-know-about
[3] Q. O’Loughlin, “Why Is Most Journalism About IQ So Bad?” Quillette – documents how media coverage understates the robustness of IQ research; notes that tests predict equally well within demographic groups. https://quillette.com/2024/10/30/why-is-most-journalism-about-intelligence-so-bad/
[4] Furnham, A. & Hughes, D. “Myths and Misconceptions About Intelligence: A Study of 35 Myths,” Personality and Individual Differences – reviews empirical literature debunking common myths (e.g., that IQ tests are culturally useless or unreliable). https://archive.jwest.org/Research/Furnham2021-MythsIntelligence.pdf