An In-Depth Examination of Student Stress Levels: A Comprehensive Analysis
Authors- Sumaiya Jamir Mulla
Abstract- This study presents a detailed analysis of student stress levels based on a comprehensive dataset gathered from undergraduate and graduate students across diverse disciplines. The dataset includes self-reported stress levels, demographic information, academic performance metrics, and factors contributing to stress. Utilizing statistical analysis techniques, including correlation analysis, regression modelling, and clustering algorithms, we uncover patterns and relationships within the dataset. Our analysis explores the impact of various factors such as academic workload, time management skills, social support networks, and coping mechanisms on student stress levels. Additionally, we investigate demographic differences in stress experiences, considering factors such as academic year. Preliminary findings reveal a complex interplay of factors influencing student stress levels. Academic workload emerges as a significant predictor of stress, with students reporting higher stress levels during peak academic periods. However, the relationship between workload and stress is moderated by factors such as time management skills and social support, highlighting the importance of individual coping strategies.
