Abstract:
Motorcycle injuries contribute a substantial number of deaths and hospital admissions in various regions in Kenya. Most riders are not properly trained and others take drugs and ride. The most dangerous part of it is that about 60% of these people who die through this kind of accidents are within the ages of 16 and 35 years, the labor force of the country. The ultimate goal of this research is to use Poisson regression to analyze the secondary data which was obtained from the Police Offices at Narok, Department of Traffic or Narok County Referral Hospital on the number of people killed or seriously injured through road accidents caused by motorcyclists in Narok from 2005 to 2014, given the ages of those who were killed, the day that the accident which killed or injured the people occurred and time (in years). Negative binomial regression analysis wasl, therefore, used to validate the Poisson regression model. The day an accident occurred was to determine the expected number of people killed in that accident. Also, the age of a person involved in this accident determined whether an individual of a certain age-group would be killed. Motorcyclists can avoid some of these accidents with proper training and shunning away from use of drugs when riding. My study will apply descriptive research to explore this analysis.
