Assessing the Variation in Academic Performance between Colleges: A Comparative Study of Graduating Students' CGPA in Joseph Sarwuan Tarka University Makurdi Using Stratified Random Sampling (2018-2022)
Year: 2025
Type: article
Study design: Observational Study
Abstract: The accuracy of Cumulative Grade Point Average (CGPA) estimates is crucial for assessing student academic performance. However, the choice of allocation method in stratified random sampling can significantly impact the precision of these estimates. This study compares the efficiency of equal and proportional allocation methods in estimating CGPA using a stratified random sampling approach. The study focuses on the College of Biological Sciences and the College of Physical Sciences at Joseph Sarwuan Tarka University Makurdi, analyzing CGPA data from ten departments over four academic sessions (2018-2022). The results showed that both methods provided reasonably stable estimates of CGPA, with minimal variation across colleges and sessions. However, equal allocation tended to provide slightly more precise estimates, as evidenced by lower variance and coefficient of variation (CV) values. The study also revealed that students from the College of Biological Sciences tended to have higher mean CGPA compared to students from the College of Physical Sciences. The findings suggest that both allocation methods can be effective in estimating CGPA, although equal allocation may have a slight advantage in terms of precision. The results highlight the importance of considering the specific research context and objectives when choosing an allocation method. This study contributes to the existing literature on sampling methods and provides insights for educators, administrators, and policymakers seeking to improve the accuracy of CGPA estimates
Authors: Tersoo UBA, Nguavese Tertsegha TIVDE
Institution: Joseph Sarwuan Tarka University Makurdi
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W4407772608