Assessment of the Proficiency of Students in the use of Mathematical and Statistical Software Packages

Proficiency with mathematical and statistical software packages is essential for solving complex problems, data analysis and interpretation in a variety of academic disciplines, especially for students enrolled in research-oriented courses. Despite their relevance, many students struggle to use these tools and packages due to lack of exposure, insufficient resources, inadequate training and availability of the software. This study identifies and assesses the socio-economic and institutional factors affecting students’ proficiency in mathematical and statistical software packages. Data were collected using a structured questionnaire and administered to 100 randomly selected students of the Department of Statistics at The Polytechnic, Ibadan, Main Campus. Data collected were analyzed using descriptive and regression analysis. Statistical Package for Social Scientists (SPSS) software was used to conduct the statistical analysis. A mathematical model was formed from the data analysis via the use of the regression analysis. Results revealed that participants were familiar with the software packages, with slight variations in usage. SPSS was familiar to 25% of the participants, MATLAB (MATrix LABoratory) to 27%, and both Python and R to 24%. The frequency of statistical package usage further highlights gaps in proficiency. This was measured on a four-point Likert scale (Rarely = 1 to Always = 4). While 42% of participants used statistical packages "Often," only 17% reported "Always" using them. Others reported more sporadic usage, with 23% using them "Sometimes" and 18% "Rarely". Regarding the availability of adequate resources for learning mathematical and statistical software packages, 60% of participants indicated that resources were provided "Often" or "Always," while 40% reported "Rarely" or "Sometimes". From the findings, efforts should be made to motivate students by raising awareness of the importance of mathematical and statistical software skills for their academic and professional success. The institution’s curriculum should be reviewed and aligned with industry demands, integrating mathematical and statistical software training as a core component.