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Burglary Crime Analysis Using Logistic Regression, Daniel Antolos, Dahai Liu, Andrei Ludu, Dennis Vincenzi
Burglary Crime Analysis Using Logistic Regression, Daniel Antolos, Dahai Liu, Andrei Ludu, Dennis Vincenzi
Andrei Ludu
This study used a logistic regression model to investigate the relationship between several predicting factors and burglary occurrence probability with regard to the epicenter. These factors include day of the week, time of the day, repeated victimization, connectors and barriers. Data was collected from a local police report on 2010 burglary incidents. Results showed the model has various degrees of significance in terms of predicting the occurrence within difference ranges from the epicenter. Follow-up refined multiple comparisons of different sizes were observed to further discover the pattern of prediction strength of these factors. Results are discussed and further research directions …
Burglary Crime Analysis Using Logistic Regression, Daniel Antolos, Dahai Liu, Andrei Ludu, Dennis Vincenzi
Burglary Crime Analysis Using Logistic Regression, Daniel Antolos, Dahai Liu, Andrei Ludu, Dennis Vincenzi
Dahai Liu