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Quantification of Human Intelligence Using Principal Component Analysis

Publication Type : Conference Paper

Publisher : Springer

Source : Lecture Notes in Networks and Systems

Url : https://doi.org/10.1007/978-981-97-2053-8_17.

Campus : Coimbatore

School : School of Physical Sciences

Department : Mathematics

Year : 2024

Abstract : Intelligence Quotient (IQ) classifies individuals into various categories based on their cognitive abilities, and it has been used for a long period of time to quantify a person’s intelligence. It has been observed that the majority of earlier studies employ IQ for diagnosis and assessment of intellectual disability but do not disclose how IQ was calculated using raw data. In this paper, we present a novel method that uses Principle Component Analysis (PCA) to quantify IQ of individuals from raw data obtained through IQ tests. The proposed method was used to examine the IQ of a subset of diverse group of individuals, rather than using a homogeneous group with a large sample size, to determine even the smallest variations in their cognitive abilities. The computational method proposed in this paper can be used a statistical tool for IQ measurement.

Cite this Research Publication : Vel Vignesh, M., Boolog, V., Bagyalakshmi, M., Thilaga, M. (2024). Quantification of Human Intelligence Using Principal Component Analysis. In: Sharma, H., Shrivastava, V., Tripathi, A.K., Wang, L. (eds) Communication and Intelligent Systems. ICCIS 2023. Lecture Notes in Networks and Systems, vol 967. Springer, Singapore. https://doi.org/10.1007/978-981-97-2053-8_17.

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