DefinePK

Abstract

This study investigates the trends and patterns of crime in Khyber Pakhtunkhwa (KP), Pakistan, over the period 2012 to 2022. Using a combination of descriptive statistics, correlation analysis, and time series forecasting (ARIMA), the research analyzes eight major crime categories: murder, attempted murder, kidnapping, robbery, burglary, Dacoity (armed robbery), cattle theft, and other theft. Data were sourced from official crime records, including Khyber Pakhtunkhwa Police reports and national statistical databases. The study identifies significant year-to-year variations and seasonality in crime patterns. Strong positive correlations were observed between certain crimes, such as murder and Dacoity, as well as burglary and robbery, indicating possible co-occurrence or common underlying factors. Conversely, crimes such as kidnapping and cattle theft demonstrated a strong negative correlation, suggesting inverse relationships in their occurrence. Stationarity tests and ARIMA modeling enabled crime forecasting from 2023 to 2027, providing insight into potential future crime rates and highlighting trends of stability or volatility in various categories. The findings aim to support policymakers, law enforcement, and researchers in developing data- driven strategies for crime prevention, resource allocation, and public safety enhancement. The research contributes to the growing body of literature on regional crime analytics and emphasizes the value of statistical tools in understanding and anticipating criminal activity.