American Journal of Applied Mathematics and Statistics
ISSN (Print): 2328-7306 ISSN (Online): 2328-7292 Website: http://www.sciepub.com/journal/ajams Editor-in-chief: Mohamed Seddeek
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American Journal of Applied Mathematics and Statistics. 2014, 2(6), 394-397
DOI: 10.12691/ajams-2-6-6
Open AccessCase Study

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

G. O. Nwafor1, and C. E Onwukwe2

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

Pub. Date: November 26, 2014

Cite this paper:
G. O. Nwafor and 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

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.

Keywords:
discriminant analysis linear classification function confusion matrix prediction rule

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