Temporal Trends of Robberies in Brooklyn, New York 2023

Abstract

Robberies are believed to be influenced by temporal trends such as time of day, day of the week, and season. To test this claim, a spatial regression analysis was performed on robberies in Brooklyn, New York for the year 2023. In 2023 a total of 4,316 robberies occurred. However, each of these robberies were sorted into the three temporal trends listed above. Time of day was sorted into morning, afternoon, or night. Day of the week was sorted into weekdays or weekends. Seasons were sorted into winter, spring, fall, and summer. After, the robbery dataset was spatially joined into the Brooklyn census tracts to run the spatial analysis. For each temporal category a local bivariate relationship model was run to determine the type of relationship between the robberies and temporal trends. An exploratory regression was also run to get the adjusted R- square values and corrected Akaike’s information criterion (AICc). After the models were run, the top neighborhoods with the highest number of robberies for each trend were reported. It was found that night robberies had the highest positive relationships in the time-of-day trend. Weekdays were found to have the highest positive relationship between time and robberies in both the day of the week trend and all other temporal trends. Spring had the highest positive relationships in the season trend. The neighborhood that had the most robberies in multiple trends was East New York. These models support the claim that robberies are influenced by temporal trends.