Volume 2, Issue 1, February 2017, Page: 22-26
Multinomial Logistic Regression Analysis of the Determinants of Students’ Academic Performance in Mathematics at Basic Education Certificate Examination
Gaspar Asampana, Department of Statistics, Bolgatanga Polytechnic, Bolgatanga, Ghana
Korah Kassim Nantomah, Department of Statistics, Bolgatanga Polytechnic, Bolgatanga, Ghana
Evans Ayagikwaga Tungosiamu, Zamse Senior High/Technical, Bolgatanga, Ghana
Received: Nov. 1, 2016;       Accepted: Dec. 14, 2016;       Published: Jan. 16, 2017
DOI: 10.11648/j.her.20170201.15      View  4137      Downloads  410
The focus of the study is to use multinomial logistic regression model to analyze the determinants of students’ academic performance in mathematics. A simple random sample of 393 students was selected from a cohort of first year students of Zamse Senior High/Technical in the Bolgatanga Municipality. The students were admitted in the 2015/2016 academic year to pursue various programmes in the school. A questionnaire was used to gather data from the students. The results indicate that the occurrence of good performance in mathematics is largely dependent on sex of students with male students showing significantly good performance than female students. Another significant predictor of good academic performance in mathematics was the age of students; with younger students exhibiting good academic performance than older students. Mother’s employment also contributes significantly to good performance in mathematics with students whose mothers are employed showing good academic performance than their counterparts whose mothers are not employed.
Basic Education Certificate Examination, Multinomial Logit Model, Academic Performance and Regression
To cite this article
Gaspar Asampana, Korah Kassim Nantomah, Evans Ayagikwaga Tungosiamu, Multinomial Logistic Regression Analysis of the Determinants of Students’ Academic Performance in Mathematics at Basic Education Certificate Examination, Higher Education Research. Vol. 2, No. 1, 2017, pp. 22-26. doi: 10.11648/j.her.20170201.15
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This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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