Analyzing the Relationship Between Social Media Usage and Suicide Rates Using Python

"Analyzing the Relationship Between Social Media Usage and Suicide Rates Using Python"
This project aims to analyze the relationship between social media usage (Twitter and Facebook user counts) and suicide rates using statistical and machine learning techniques. The analysis explores correlations and builds a regression model to understand how changes in Twitter and Facebook user counts influence suicide rates.

Objectives:

1. Correlation Analysis:
   To determine the strength and nature of the relationship between the number of Twitter and Facebook users and suicide rates. Both Pearson and Spearman correlation methods are applied to assess linear and monotonic relationships, respectively.

2. Regression Analysis:
   To build a multiple regression model that evaluates the combined and individual effects of Twitter and Facebook user counts on suicide rates. The regression results provide insight into which platform has a stronger impact.

3. Comparative Analysis:
   To identify whether Twitter or Facebook has a stronger relationship with suicide rates by comparing regression coefficients.