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Huberty C J, Barton R M “an introduction to discriminant analysis Measurement and evaluations in counseling and development” 22: 158-168. 1989.

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Article

On Proper Classification and Placement of Students in Nigerian University Systems Using Discriminant Analysis

1Department of Mathematics and Statistics, Cross River University of Technology Calabar, Nigeria

2Department of Mathematics, Statistics and Computer Science, University of Calabar, Cross River State, Nigeria


American Journal of Applied Mathematics and Statistics. 2014, Vol. 2 No. 6, 394-397
DOI: 10.12691/ajams-2-6-6
Copyright © 2014 Science and Education Publishing

Cite this paper:
G. O. Nwafor, C. E Onwukwe. On Proper Classification and Placement of Students in Nigerian University Systems Using Discriminant Analysis. American Journal of Applied Mathematics and Statistics. 2014; 2(6):394-397. doi: 10.12691/ajams-2-6-6.

Correspondence to: G.  O. Nwafor, Department of Mathematics and Statistics, Cross River University of Technology Calabar, Nigeria. Email: gonwafor@gmail.com

Abstract

This paper attempts to provide more realistic and reliable way of placing Nigerian students seeking admission into Nigerian University system using Discriminant Analysis and also providing quantitative analysis of a Discriminant Analysis approach to prediction of student’s admission scores into a university system. The paper utilizes secondary data sourced from the Admission and Public Relation Department of Cross Rivers University of Technology Calabar, the conditions for predictive and classification discriminant analysis were obtained, and the empirical result yield a discriminant linear classification function results on the various faculties of interest on the method of admission system obtainable in Nigeria university system. The study reveals university mandatory examination (UME) and Aptitude Test score of students in their various faculties. The linear function established a hit ratio of 83% of which successfully predicted the student admission scores. The study had apparent error rate of 17% which explains the probabilities of misclassification.

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