Principal Component Analysis for Investigating the Relationship between the Semester Results and Academic Performance of Students in a Polytechnic in Niger State, Nigeria

S.S. Ahmed, E. M. Yisa, M. Jibrin, G. Yahaya
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Abstract

Factor analysis permits the ability to simplify a set of complex variables using statistical procedures to explore the underlying dimensions that explain the relationships between the multiple variables. This paper therefore used factor analysis to investigate the relationship between the semester results and academic performance of students at a centre for continuing education and training in a Polytechnic in Niger State, Nigeria using principal component method after collecting data from 57 students. The findings of this study revealed that there is weak linear relationship between the variables. From the total variance explained table, 4 factors were extracted which accounted for 60.7% and the remaining factors only accounted for 39.3% of variation. Data obtained observed that Component 1 loads high on BAM225=0.625, Component 2 loaded as high as 0.549 for STP213, while Component 3 loaded for GNS201= 0.681 and Component 4 loads on GLTVII = 0.586. The results could signify the existence of these factors significantly contributing to the academic performance of students in polytechnic.
用主成分分析法研究尼日利亚尼日尔州一所理工学院学生的学期成绩与学习成绩之间的关系
因子分析能够利用统计程序简化一组复杂的变量,从而探索解释多个变量之间关系的基本维度。因此,本文在收集了 57 名学生的数据后,采用主成分分析法研究了尼日利亚尼日尔州一所理工学院继续教育与培训中心学生的学期成绩与学习成绩之间的关系。研究结果表明,变量之间的线性关系较弱。从总变异解释表中,提取了 4 个因子,占 60.7%,其余因子仅占变异的 39.3%。数据显示,成分 1 在 BAM225 上的载荷为 0.625,成分 2 在 STP213 上的载荷高达 0.549,而成分 3 在 GNS201 上的载荷为 0.681,成分 4 在 GLTVII 上的载荷为 0.586。这些结果表明,这些因素对理工学院学生的学业成绩有重大影响。
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