Using binary logistic regression in predicting traffic accidents in Algeria

Abstract

This research aims to estimate the probability of traffic accidents in Algeria, where binary logistic regression was used for a sample of 1666 car insurance contracts from CASH during the period 2016-2018. The results of the analytical study showed that the human factor is the first factor leading to traffic accidents in urban areas by more than 95%, and the results of the econometrics study showed the effect of gender (SE) and age of the vehicle (AGV) on the probability of predicting traffic accidents in the selected study sample. . Where the chance of a traffic accident in males is 0.547 Once greater than the chance of a traffic accident in females. And that a one-degree increase in the life of the car will increase the possibility of a traffic accident occurring or not by 0.942 Once.