Abstract

This aim of this study was to determine what affects aggregate crime rates around the world. This thesis used Mathematical Modeling techniques to build generalized linear models for homicide rates and burglary and housebreaking rates using the following predictive factors: economic indicators, education rates, government quality indicators, ethno-linguistic fractionalization, GDP per capita and its growth, drug consumption rates, and age and gender ratios. We used a series of factor selection techniques including linear and stepwise regressions, principal component analysis, and regression analysis to select factors to use to build final models of homicide and burglary and housebreaking.

Advisor

Pasteur, Drew

Department

Mathematics

Publication Date

2018

Degree Granted

Bachelor of Arts

Document Type

Senior Independent Study Thesis

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© Copyright 2018 Kelly M. Steurer