This study evaluates the application of descriptive and inferential statistics in graduate research at DMMMSU-CGS. Findings show that while nominal and interval/ratio scales are often treated with appropriate measures (frequency counts and means), ordinal data is fre-quently misrepresented using the mean instead of median or mode. Such lapses compromise validity and highlight gaps in statistical literacy. This misuse underscores the need for statistical diagnostics prior to test se-lection and the inclusion of assumption checks in research guidelines. Moreover, analysis of appropriateness and accuracy revealed that while proper methods generally produce accurate results, some accuracy still arises from misapplied tools due to compensating factors. These findings stress the importance of enhanced statistical training and methodological rigor.