Predicting Crime in Boston
Data Science Project, Fall 2019
Instructor: Pavlos Protopapas, Kevin A. Rader, Chris Tanner
Collaborator: Ethan Kim, Jimmy Qin, Jack Wongtam
Location: Cambridge, MA
Project Goals
High level question: What geographic and socioeconomic factors are associated with which types of crimes? What are the associations (linear, etc.)?
Low level question 1: What is the relationship, if any, between types of crime and proximity of the crime to the nearest streetlight? What about proximity to other common landmarks such as libraries, schools, and Hubway stations?
Low level question 2: What is the relationship, if any, between inequality and types of crime? We use income, Gini coefficient, and property values as proxy measures of inequality.
Full report available: https://sites.google.com/view/predictcrimebostonlyh/home
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