Philippine E-Journals

University Student'S Competence In Performing Statistical Analysis

Princess Jhoie C. Corpuz | Melissa B Bacena

Discipline: Mathematics

 

Abstract:

Statistical analysis gained increasing relevance in research writing, playing a pivotal role in students' research endeavors. It makes research more scientific and objective. However, many students find it challenging to conduct statistical analyses. In line with this, this study aimed to assess the students' competence level and their challenges encountered in performing statistical analysis in research writing. The research employed a cross-sectional quantitative design using a survey method. The study was conducted at the University of La Salette, Inc., Dubinan East, Santiago City, Isabela, during the second semester of the academic year 2024–2025. A total of 285 undergraduate students enrolled in the Research Writing subject participated in the study, selected through stratified sampling from different academic departments. Data were gathered using a researcher-made questionnaire that measured students' demographic profile, level of competence, and challenges encountered in statistical analysis. The instrument was contentvalidated by experts and demonstrated high reliability (Cronbach's alpha = 0.959). Statistical analyses were performed using SPSS, including descriptive statistics, Mann–Whitney U tests, Kruskal–Wallis H tests, and post hoc analyses. Findings revealed that students demonstrated a competent level of performance across areas: basic statistical knowledge, data cleaning and preparation, software proficiency, and interpretation skills, with an overall mean of 2.90. Data cleaning and preparation emerged as the strongest area, while software proficiency and interpretation skills showed relatively lower mean scores. Despite being generally competent, students perceived all areas of statistical analysis as challenging, particularly data cleaning and preparation, interpretation of results, and the application of advanced statistical procedures using software. There is no significant difference in students' competence level when grouped by department, year level, or sex. However, students who had prior exposure to a statistical course demonstrated significantly higher competence across all areas. Moreover, software proficiency significantly differed based on the statistical software used, with students utilizing both Microsoft Excel and SPSS exhibiting the highest competence. In conclusion, while students possess adequate statistical competence, they continue to face significant challenges. The study recommends strengthening hands-on statistical training, integrating applied statistics across research courses, and increasing students' exposure to multiple statistical software tools to enhance their competence further and reduce challenges in statistical analysis.