Crime in Trinidad and Tobago: A Data-Driven Statistical Analysis

We investigate trends in crime in Trinidad and Tobago using a data-driven approach
to understand temporal trends and socioeconomic drivers of major offenses such as
murder, robbery, and larceny. The analysis integrated official police crime records,
national census data, and employed time-series visualization, regression modeling,
and normalization techniques to uncover patterns and insights related to fluctuations
in crime rates and their correlation with social vulnerability factors. Results indicated
that temporal trends, population-normalized rates, and predictive policing forecasts
contributed to a clearer understanding of how socioeconomics and public safety shaped
national crime dynamics. This research demonstrated how data science methods can
support evidence-based reasoning in the study of criminology.