4.7 Article

A study of academic performance of business school graduates using neural network and statistical techniques

Journal

EXPERT SYSTEMS WITH APPLICATIONS
Volume 36, Issue 4, Pages 7865-7872

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2008.11.003

Keywords

Academic performance; Discriminant analysis; Logistic regression; Neural network; Regression analysis

Funding

  1. Council of Scientific and Industrial Research, India [25 (0137)/05/EMR-II]

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Over the past several years, there is tremendous increase in the number of applicants to business schools and hence adequately measuring the potential of these Students with regard to their academic performance is an important process of admission decision for any business school. In the present study, an analysis is carried Out to predict the academic performance of business school graduates using neural networks and traditional statistical techniques and results are compared to evaluate the performance of these techniques. The underlying constructs in a traditional business school curriculum are also identified and its relevance with the various elements of admission process is presented. (C) 2008 Elsevier Ltd. All rights reserved.

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