Modelling Fatalities Associated With Road Traffic Accidents And Other Factors Using Poisson Model

dc.contributor.author	Macharia, Kimani Kevin
dc.date.accessioned	2019-10-31T06:06:23Z
dc.date.available	2019-10-31T06:06:23Z
dc.date.issued	2019
dc.identifier.uri	http://erepository.uonbi.ac.ke/handle/11295/107307
dc.description.abstract	According to the World Health Organization (WHO, 2018), 1.35 million people died in 2016 on the world’s roads, with road tra c injuries being the leading cause of death for children and young adults aged 5􀀀29 years. Road tra c injuries is ranked 8th in the leading causes of death for all ages in 2016.It surpasses those dying from HIV/AIDS, tuberculosis and diarrhoeal diseases although the political commitment and nancial investments in road safety is only a fraction of that made to combat these diseases (WHO, 2018). The objectives of the study were to determine factors associated with fatal Road Tra c Accidents (RTAs) in Kenya and to determine which of the poisson model t the RTA fatalities count data better.	en_US
dc.language.iso	en	en_US
dc.publisher	UoN	en_US
dc.rights	Attribution-NonCommercial-NoDerivs 3.0 United States	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.title	Modelling Fatalities Associated With Road Traffic Accidents And Other Factors Using Poisson Model	en_US
dc.type	Thesis	en_US

Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 United States