Studying Correlations between Genetic Variation and Test Score Gaps

Gregory Connor, John G.R. Fuerst (Herausgeber)

Buch | Softcover

359 Seiten

2024 | Unabridged edition
Cambridge Scholars Publishing (Verlag)
978-1-5275-7566-0 (ISBN)

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This book is an edited collection of recently published papers on the sources of average test score gaps when analysed through the lenses of race and ethnicity, socio-economic status, and biogeographic ancestries such as European, African, and East Asian ancestry. It brings together exciting recent findings that rely on powerful DNA-based methods developed in the last few decades. The book also considers the public policy question as to whether, and how, these findings should be disseminated to the general public audience.

Gregory Connor recently retired from his position as Professor of Finance at Maynooth University (Ireland). He previously taught at the London School of Economics (UK), the University of California-Berkeley (USA), and Northwestern University (USA). He has published widely and is co-author (with Robert Korajczyk and Lisa Goldberg) of Financial Risk Analysis. His research focusses on factor modelling with large cross-sections applied to macro-finance, genome-wide association studies (GWAS), the g-factor, and gene/environment analysis of variance (ANOVA).John Fuerst has previously conducted research at Cleveland State University (USA), North Carolina State University (USA), and Case Western Reserve University (USA). He is currently enrolled in a post graduate programme in bioinformatics and has previously done graduate work in psychology. His research focusses on behavioural genetics, psychometrics, genome-wide association studies (GWAS), and differential psychology.

Erscheinungsdatum	05.03.2024
Verlagsort	Newcastle upon Tyne
Sprache	englisch
Maße	148 x 212 mm
Themenwelt	Geisteswissenschaften ► Psychologie ► Pädagogische Psychologie
Themenwelt	Sozialwissenschaften ► Pädagogik
ISBN-10	1-5275-7566-7 / 1527575667
ISBN-13	978-1-5275-7566-0 / 9781527575660
Zustand	Neuware