Analyzing Socioeconomic Effects on Suicide Rates

Inspiration: Suicide is a global crisis linked to socioeconomic factors. Our goal is to analyze data-driven insights to inform prevention strategies.

What it does: It examines correlations between socioeconomic stressors (poverty, unemployment, inflation) and suicide rates to identify high-risk groups.

How we built it: We collected global datasets, cleaned and analyzed them using statistical models and time series to uncover patterns and inform policy recommendations.

Challenges: Data limitations, underreporting, cultural differences, and ethical considerations in addressing a sensitive issue.

Accomplishments: Successfully integrated diverse data, built predictive models, and provided insights for policymakers.

What we learned: Economic instability significantly impacts suicide rates, highlighting the need for better data reporting and intervention strategies.

What’s next: Expanding data sources, refining models, simulating policy impacts, and collaborating on public awareness initiatives.

Built With

• rstudio
• vscode