Related Experiment Video
Updated: Jul 16, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Application patterns when applicants know the odds: implications for selection research and practice
Nathan R Kuncel1, David M Klieger
1Department of Psychology, University of Minnesota, Minneapolis, MN 55455, USA. kunce001@umn.edu
Abstract:
Unlike previous research that found small differences between population standard deviations and applicant pool standard deviations (P. R. Sackett & D. J. Ostgaard, 1994; D. S. Ones & C. Viswesvaran, 2003), this study revealed a 23% disparity between Law School Admission Test (LSAT) scores of all LSAT test takers and those of LSAT test takers who applied to law school. This study also illustrated robust applicant self-selection behavior across different law school ranks. These findings are important, because predictor scores of applicants who know their scores in advance and perceive small selection ratios necessitate substantially smaller range restriction corrections than those that would be required by population standard deviations. Furthermore, these findings more generally reveal that applicants who know their scores in advance behave quite differently from applicants who do not.
Related Concept Videos
Confirmation Biases
Odds Ratio
Bias
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
Stereotype Threat and Self-fulfilling Prophecies
Halo Effect
Types of Selection