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November 2016 Survivor rates of new entrants into an undergraduate degree programme under clearance uncertainty
Virtue U. EKHOSUEHI, Francis O OYEGUE
Afr. J. Appl. Stat. 3(1): 59-67 (November 2016). DOI: 10.16929/ajas/2016.57.201

Abstract

Considering the clearance exercise in a Nigerian university setting, this study attempts to answer the question of the following sort: ‘ What is the survivor rate of candidates offered (provisional) admission into a course of study in the face of clearance uncertainty?’ We represent the problem as a system of differential equations within the framework of a network model with constant risk and then solve it using the Laplace transform. Rather than relying on steady-states fractional flow rates, we provide a transient solution to the problem. The survivor function for each entry level derived for the problem sheds some light on situations where a decision is to be made on two (or more) preferred courses and thus evades possible trauma in the application process.

Cette étude prend place dans la problématique de l'admission des étudiants dans les universités nigériannes. Elle se propose de répondre aux questions semblables à celle-ci : quel est le taux de survie (final) des candidats provisoirement admis à un programme dans une situation d'admission finale incertaine? Nous modélisons ce problème grâce à un système d'équations différentielles dans le cadre d'un modèle de réseau à risque constant. La transformation de Laplace est notre outil pour résoudre le problème théorique.

Citation

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Virtue U. EKHOSUEHI. Francis O OYEGUE. "Survivor rates of new entrants into an undergraduate degree programme under clearance uncertainty." Afr. J. Appl. Stat. 3 (1) 59 - 67, November 2016. https://doi.org/10.16929/ajas/2016.57.201

Information

Published: November 2016
First available in Project Euclid: 16 May 2019

Digital Object Identifier: 10.16929/ajas/2016.57.201

Subjects:
Primary: 97K80, 97M40

Rights: Copyright © 2016 The Statistics and Probability African Society

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Vol.3 • No. 1 • November 2016
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