Predicting students' success at pre-university studies using linear and logistic regressions

Noor Azizah Suliman, Basir Abidin, Norhafizah Abdul Manan, Ahmad Mahir Razali

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The study is aimed to find the most suitable model that could predict the students' success at the medical pre-university studies, Centre for Foundation in Science, Languages and General Studies of Cyberjaya University College of Medical Sciences (CUCMS). The predictors under investigation were the national high school exit examination-Sijil Pelajaran Malaysia (SPM) achievements such as Biology, Chemistry, Physics, Additional Mathematics, Mathematics, English and Bahasa Malaysia results as well as gender and high school background factors. The outcomes showed that there is a significant difference in the final CGPA, Biology and Mathematics subjects at pre-university by gender factor, while by high school background also for Mathematics subject. In general, the correlation between the academic achievements at the high school and medical pre-university is moderately significant at α-level of 0.05, except for languages subjects. It was found also that logistic regression techniques gave better prediction models than the multiple linear regression technique for this data set. The developed logistic models were able to give the probability that is almost accurate with the real case. Hence, it could be used to identify successful students who are qualified to enter the CUCMS medical faculty before accepting any students to its foundation program.

Original languageEnglish
Title of host publicationStatistics and Operational Research International Conference, SORIC 2013
PublisherAmerican Institute of Physics Inc.
Pages306-316
Number of pages11
Volume1613
ISBN (Electronic)9780735412491
DOIs
Publication statusPublished - 1 Jan 2014
EventStatistics and Operational Research International Conference, SORIC 2013 - Sarawak, Malaysia
Duration: 3 Dec 20135 Dec 2013

Other

OtherStatistics and Operational Research International Conference, SORIC 2013
CountryMalaysia
CitySarawak
Period3/12/135/12/13

Fingerprint

logistics
students
regression analysis
mathematics
medical science
Malaysia
biology
predictions
examination
chemistry
physics

Keywords

  • linear regression
  • logistic regression
  • medical foundation
  • pre-university
  • prediction

ASJC Scopus subject areas

  • Physics and Astronomy(all)

Cite this

Suliman, N. A., Abidin, B., Manan, N. A., & Razali, A. M. (2014). Predicting students' success at pre-university studies using linear and logistic regressions. In Statistics and Operational Research International Conference, SORIC 2013 (Vol. 1613, pp. 306-316). American Institute of Physics Inc.. https://doi.org/10.1063/1.4894355

Predicting students' success at pre-university studies using linear and logistic regressions. / Suliman, Noor Azizah; Abidin, Basir; Manan, Norhafizah Abdul; Razali, Ahmad Mahir.

Statistics and Operational Research International Conference, SORIC 2013. Vol. 1613 American Institute of Physics Inc., 2014. p. 306-316.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Suliman, NA, Abidin, B, Manan, NA & Razali, AM 2014, Predicting students' success at pre-university studies using linear and logistic regressions. in Statistics and Operational Research International Conference, SORIC 2013. vol. 1613, American Institute of Physics Inc., pp. 306-316, Statistics and Operational Research International Conference, SORIC 2013, Sarawak, Malaysia, 3/12/13. https://doi.org/10.1063/1.4894355
Suliman NA, Abidin B, Manan NA, Razali AM. Predicting students' success at pre-university studies using linear and logistic regressions. In Statistics and Operational Research International Conference, SORIC 2013. Vol. 1613. American Institute of Physics Inc. 2014. p. 306-316 https://doi.org/10.1063/1.4894355
Suliman, Noor Azizah ; Abidin, Basir ; Manan, Norhafizah Abdul ; Razali, Ahmad Mahir. / Predicting students' success at pre-university studies using linear and logistic regressions. Statistics and Operational Research International Conference, SORIC 2013. Vol. 1613 American Institute of Physics Inc., 2014. pp. 306-316
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