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Non-g residuals of group factors predict ability tilt, college majors, and jobs: A non-g nexus

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  • Coyle, Thomas R.

Abstract

This study examined the predictive power of non-g residuals of group factors (based on multiple tests) for diverse criteria (e.g., aptitude tests, college majors, occupations). Test scores were drawn from the National Longitudinal Survey of Youth (N=1950). Four group factors (math, verbal, speed, shop/technical) were estimated using the Armed Services Vocational Aptitude Battery, a diverse battery of 12 cognitive tests. The residuals of the group factors were estimated after removing g (variance common to all tests) and were correlated with aptitude test scores (SAT, ACT, PSAT), ability tilt (i.e., difference between math and verbal scores on the aptitude tests), and college majors and jobs in science, technology, engineering, and math (STEM) and the humanities. The math residuals correlated positively with math/STEM criteria and negatively with verbal/humanities criteria. In contrast, the verbal residuals showed the opposite pattern. The residuals of the two non-academic factors (speed and shop) generally correlated negligibly with all criteria. The results are the first to demonstrate the predictive power of group factor residuals for diverse criteria. The findings extend prior research on non-g factors for individual tests (SAT and ACT) and provide evidence of a non-g nexus involving group factors. The pattern of results supports investment theories, which predict that investment in one area (math) correlates positively with complementary criteria (math/STEM) but negatively with competing criteria (verbal/humanities).

Suggested Citation

  • Coyle, Thomas R., 2018. "Non-g residuals of group factors predict ability tilt, college majors, and jobs: A non-g nexus," Intelligence, Elsevier, vol. 67(C), pages 19-25.
    • Handle: RePEc:eee:intell:v:67:y:2018:i:c:p:19-25
    DOI: 10.1016/j.intell.2017.12.003
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    Cited by:

    1. Coyle, Thomas R., 2022. "Sex differences in spatial and mechanical tilt: Support for investment theories," Intelligence, Elsevier, vol. 95(C).
    2. Benjamin Artz & Colin P. Green & John S. Heywood, 2021. "Does performance pay increase alcohol and drug use?," Journal of Population Economics, Springer;European Society for Population Economics, vol. 34(3), pages 969-1002, July.
    3. Zullo, Matteo, 2022. "(No) Trade-off between numeracy and verbal reasoning development: PISA evidence from Italy's academic tracking," Intelligence, Elsevier, vol. 95(C).
    4. Coyle, Thomas R., 2023. "Sex differences in tech tilt and academic tilt in adolescence: Processing speed mediates age-tilt relations," Intelligence, Elsevier, vol. 100(C).
    5. Coyle, Thomas R. & Greiff, Samuel, 2021. "The future of intelligence: The role of specific abilities," Intelligence, Elsevier, vol. 88(C).
    6. Wai, Jonathan & Hodges, Jaret & Makel, Matthew C., 2018. "Sex differences in ability tilt in the right tail of cognitive abilities: A 35-year examination," Intelligence, Elsevier, vol. 67(C), pages 76-83.
    7. Loehlin, John C., 2019. "Cognitive clustering—How general?," Intelligence, Elsevier, vol. 75(C), pages 19-22.
    8. Becker, David & Coyle, Thomas R. & Minnigh, Tyler L. & Rindermann, Heiner, 2022. "International differences in math and science tilts: The stability, geography, and predictive power of tilt for economic criteria," Intelligence, Elsevier, vol. 92(C).
    9. Coyle, Thomas R., 2020. "Sex differences in tech tilt: Support for investment theories," Intelligence, Elsevier, vol. 80(C).
    10. Wai, Jonathan & Lee, Matthew H. & Kell, Harrison J., 2022. "Distributions of academic math-verbal tilt and overall academic skill of students specializing in different fields: A study of 1.6 million graduate record examination test takers," Intelligence, Elsevier, vol. 95(C).
    11. Coyle, Thomas R., 2019. "Tech tilt predicts jobs, college majors, and specific abilities: Support for investment theories," Intelligence, Elsevier, vol. 75(C), pages 33-40.
    12. Coyle, Thomas R. & Greiff, Samuel, 2023. "Carbon is to life as g is to _____: A review of the contributions to the special issue on specific abilities in intelligence," Intelligence, Elsevier, vol. 101(C).

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