"General Intelligence," Objectively Determined and Measured

Spearman, C.

doi:10.2307/1412107

Cited by 4,797 publications

(2,197 citation statements)

References 0 publications

Supporting

Mentioning

2,036

Contrasting

Unclassified

114

Order By: Relevance

“…To verify our results, we investigated the behaviour of the correlation using Tycho-2 data instead of Kharchenko (2001) data, which led to the same conclusions. Furthermore, we employed the Spearman rank-order correlation coefficient (Spearman 1904), a non-parametric measure of correlation, to investigate our results. For this, we divided our sample (Table 2) The two reddened samples show, with almost 100% probability, that there is a weak correlation that is not due to random sampling.…”

Section: Statistical Analysesmentioning

confidence: 99%

A search for photometric variability in magnetic chemically peculiar stars using ASAS-3 data

Bernhard

Hümmerich

Otero

et al. 2015

A&A

View full text Add to dashboard Cite

Context. The (magnetic) chemically peculiar (CP) stars of the upper main sequence are well-suited laboratories for investigating the influence of magnetic fields on the stellar surface because they produce abundance inhomogeneities (spots), which results in photometric variability that is explained in terms of the oblique rotator model. CP stars exhibiting this phenomenon are normally classified as α 2 Canum Venaticorum (ACV) variables. It is important to increase the sample of known rotational periods among CP stars by discovering new ACV variables. An increased sample size will contribute to the understanding of the CP stars' evolution in time. Aims. We aim at discovering new ACV variables in the public data of the third phase of the All Sky Automated Survey (ASAS-3). Furthermore, by analysis of the available photometric data, we intend to derive rotational periods of the stars. Methods. The ASAS-3 data were cross-correlated with the Catalogue of Ap, HgMn, and Am stars in order to analyse the light curves of bona fide CP and related stars. The light curves were downloaded and cleaned of outliers and data points with a flag indicating bad quality. Promising candidates showing a larger scatter than observed for constant stars in the corresponding magnitude range were searched for periodic signals using a standard Fourier technique. Objects exhibiting periodic signals well above the noise level were considered and visually inspected, whereas borderline cases were rejected. Results. In total, we found 323 variables, from which 246 are reported here for the first time, and 77 were probably wrongly classified before. The observed variability pattern of most stars is in accordance with an ACV classification. For some cases, it is difficult to distinguish between the light curves of double-waved ACVs and the variability induced by orbital motion (ellipsoidal variables/eclipsing variables), especially for objects exhibiting very small amplitudes and/or significant scatter in their light curves. Thus, some eclipsing or rotating ellipsoidal variables might be present. However, we are confident that the given periods are the correct ones. There seems to be a possible weak correlation between the rotational period and colour, in the sense that cooler magnetic CP stars rotate more slowly. However, this correlation seems to disappear when correcting for the interstellar reddening. Conclusions. The next steps have to include a compilation of all available rotational periods from the literature and a detailed investigation of the astrophysical parameters of these stars. This includes a determination of the individual masses, luminosities, ages, and inclination angles. However, this information cannot be straightforwardly determined from photometric data alone.

show abstract

Section: Statistical Analysesmentioning

confidence: 99%

A search for photometric variability in magnetic chemically peculiar stars using ASAS-3 data

Bernhard

Hümmerich

Otero

et al. 2015

A&A

View full text Add to dashboard Cite

show abstract

“…The word 'intelligence' has so many connotations that the symbol 'g' was proposed nearly a century ago to denote the operational definition of intelligence as a 'general cognitive ability' representing the substantial covariance among diverse tests of cognitive abilities such as abstract reasoning, spatial, verbal and memory abilities. 5 In a meta-analysis of 322 studies, the average correlation among such diverse tests is about 0.30 6 and a general factor (first unrotated principal component) typically accounts for about 40% of the tests' total variance. 7 As discussed below, multivariate genetic analysis shows that the genetic overlap among cognitive tests is twice as great as the phenotypic overlap, suggesting that g is where the genetic action is.…”

mentioning

confidence: 99%

Genetics, genes, genomics and g

Plomin

2003

Mol Psychiatry

View full text Add to dashboard Cite

“…Examining individual differences in educational outcomes and predicting academic success has been the principal objective of developing cognitive ability tests (Spearman, 1904;Ackerman & Heggestad 1997). In assessing the predictive validity of intelligence tests, educational achievement is the primary target (Deary, Strand, Smith, & Fernandes, 2007).…”

Section: Intelligence-achievement Relationmentioning

confidence: 99%

Intelligence and Its Relationship to Achievement

Kaya¹,

Juntune²,

Stough³

2015

İlköğretim Online

View full text Add to dashboard Cite

ABSTRACT. This comprehensive literature review examines the link between intelligence and achievement. It also provides a brief summary of selected psychometric theories of intelligence. In attempt to gather all relevant scholarly literature, several procedures were used. A search of the key terms in the ERIC, PsycINFO, and Google Scholar databases was performed. The literature evidences that verbal abilities have stronger correlation with academic achievement than nonverbal abilities. Furthermore, verbal abilities are related to readiness to learn while nonverbal abilities are related to potential to learn. If intelligence scores are used to predict any kind of future academic performance, both verbal (readiness) and nonverbal (potential) abilities should be evaluated. Besides, in order to identify gifted and talented students, assessment of verbal abilities should accompany with the assessment of nonverbal abilities so that they will be able to survive in advanced academic programs.

show abstract

"General Intelligence," Objectively Determined and Measured

Cited by 4,797 publications

References 0 publications

A search for photometric variability in magnetic chemically peculiar stars using ASAS-3 data

A search for photometric variability in magnetic chemically peculiar stars using ASAS-3 data

Genetics, genes, genomics and g

Intelligence and Its Relationship to Achievement

Contact Info

Product

Resources

About