Disciplines
Applied Statistics | Criminal Law | Data Science | Law and Psychology | Law Enforcement and Corrections | State and Local Government Law | Statistical Methodology
Abstract (300 words maximum)
The recent cases of law enforcement using lethal force in the United States have gained massive public attention. My dataset is from the Mapping Police Violence website. The website’s focus was to create a heat map to display where police killings occurred most frequently. The website has a dataset with information on 7,664 deaths of suspects. The variables in the dataset include age, sex and race of the suspect; geographic location; alleged threat level; alleged weapon; cause of death; and criminal charges against the officer. In addition, the variables include whether the individual had a mental illness, was armed or was fleeing; whether video exists; whether the officer was off-duty; and whether or not the shooting was justified. The goal of my research is to examine the possible variables that could lead a police officer to kill someone. Do any of the variables listed above predict whether a police incident results in a killing? In addition, I will be looking at relationships between the predictor variables. Does sex or race predict whether the suspect is perceived as a threat? Are some ethnic groups more often killed than others? What variables predict that a person will flee from the police? What variables are associated with mental illness or drug use? Do any variables predict whether the victim was armed? These questions will be investigated with non-parametric and parametric hypothesis tests including post hoc comparisons. The findings will be summarized with stacked bar charts and stratified boxplots. Through heightened understanding of the relationships and predictors, I hope to identify ways to improve police training to prevent police incidents from turning into a killing.
Academic department under which the project should be listed
CCSE - Data Science and Analytics
Primary Investigator (PI) Name
Susan Mathews Hardy
Included in
Applied Statistics Commons, Criminal Law Commons, Data Science Commons, Law and Psychology Commons, Law Enforcement and Corrections Commons, State and Local Government Law Commons, Statistical Methodology Commons
Death by Police: When “Protecting and Serving” Goes Wrong
The recent cases of law enforcement using lethal force in the United States have gained massive public attention. My dataset is from the Mapping Police Violence website. The website’s focus was to create a heat map to display where police killings occurred most frequently. The website has a dataset with information on 7,664 deaths of suspects. The variables in the dataset include age, sex and race of the suspect; geographic location; alleged threat level; alleged weapon; cause of death; and criminal charges against the officer. In addition, the variables include whether the individual had a mental illness, was armed or was fleeing; whether video exists; whether the officer was off-duty; and whether or not the shooting was justified. The goal of my research is to examine the possible variables that could lead a police officer to kill someone. Do any of the variables listed above predict whether a police incident results in a killing? In addition, I will be looking at relationships between the predictor variables. Does sex or race predict whether the suspect is perceived as a threat? Are some ethnic groups more often killed than others? What variables predict that a person will flee from the police? What variables are associated with mental illness or drug use? Do any variables predict whether the victim was armed? These questions will be investigated with non-parametric and parametric hypothesis tests including post hoc comparisons. The findings will be summarized with stacked bar charts and stratified boxplots. Through heightened understanding of the relationships and predictors, I hope to identify ways to improve police training to prevent police incidents from turning into a killing.