A study on US Mass Shooting using data analysis and machine learning

Abstract

 Many years ago, mass shootings have become one major problem in our country. In 2021, more than 45,000 people were murdered in mass shootings. And I started to wonder, why are people doing this? If we can get some clues with existing data, it might help prevent future tragedies from happening.    

In many shooting incidents, the shooters seem to massacre without any reason. Many people wonder if it’s related to the murderer’s mental health. I started to gather some data and found two datasets about mass shootings and mental health on Kaggle, a public data-sharing website. First, I performed data analysis and statistical testing with the two datasets To further investigate the relationship between mass shootings and mental health, I fitted a linear regression model with the merged datasets. I found out that there’s an obvious correlation between these two variables, which means mental illness was one of the direct reasons that caused mass shootings. 

In addition, I want to help people avoid mass shootings. So I made a linear regression model, which helps to predict how many total victims there will be based on input factors, like location, race, age, etc. Using this model, people can put more security in dangerous locations to best avoid mass shootings.