Student Mental Health Analysis

Power BI Data Cleaning Statistical Analysis Public Health

Project Overview

This analysis explores the intricate relationship between student demographics, lifestyle choices, and mental health outcomes. Using a comprehensive survey dataset, we investigate how academic pressure, sleep patterns, and social factors correlate with depression and anxiety among university students.

Source Kaggle (Public Domain CC0)
Focus Academic Success & Well-being

Data Specs

  • Demographic Variables
  • Lifestyle & Sleep Metrics
  • Psychometric Indicators
  • Academic Performance (CGPA)

Interactive Power BI Dashboard

Key Research Findings

The Sleep-Performance Link

Strong positive correlation identified between CGPA and sleep duration; top-performing students average more rest.

Athletic Buffering

Participation in sports acts as a protective factor, correlating with significantly lower reports of depression.

Year-over-Year Stress

Anxiety and depression metrics show an upward trend as students progress into senior academic years.

Coping Mechanisms

Religious activities correlate with lower anxiety, while online entertainment shows higher isolation scores.

Database Schema & Modeling

Power BI Data Model