Mental health has become a pressing concern in contemporary society, particularly due to challenges in maintaining a healthy work-life balance. This study endeavors to address the dearth of research concerning the statistical analysis of SDFs (e.g., gender, employment status, age, education) and MHIs (e.g., mental stress, depression) among student populations. While previous studies have predominantly focused on adults, our investigation seeks to fill this gap by conducting a comprehensive analysis of these factors among students. Utilizing a student well-being dataset, we prepared the dataset and examined four combinations of independent dichotomous variables such as gender and mental stress, employment and depression, living status and family stress, and medication and anxiety. The associations between categorical variables were scrutinized using the Chi-Square Test (CST) and Fisher’s Exact Test (FST). Our findings reveal significant correlations between certain SDFs and MHIs, unfolding the complex interplay between individual characteristics and mental well-being. These findings underscore the importance of addressing work-life balance issues and implementing targeted interventions to support mental health in student populations.