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dc.contributor.advisorRekab, Kamel
dc.contributor.advisorBowles, Doug (Douglas Henri), 1952-
dc.contributor.authorEkpoh, Yawo Mawuli
dc.date.issued2020
dc.date.submitted2020 Summer
dc.descriptionTitle from PDF of title page viewed August 31, 2020
dc.descriptionDissertation advisor: Kamel Rekab and Douglas Bowles
dc.descriptionVita
dc.descriptionIncludes bibliographical references (pages 82-87)
dc.descriptionThesis (Ph.D.)--Department of Mathematics and Statistics and Social Sciences Consortium. University of Missouri--Kansas City, 2020
dc.description.abstractAfrica that is known for the birthplace of humanity has become a continent of all kind of devastating conflicts. This is a major concern because these conflicts are having lasting negative impact on the socioeconomic development of the continent and can lead to its gradual destruction with irreparable consequences such as the loss of African diverse cultures, values and traditions. Thus, it becomes urgent to understand the complexity and the dynamics of conflicts in Africa from different perceptive in order to handle conflict issues effectively and efficiently. Our statistical study primary goal is to bring Africa complex issues structure to a simple one in order to uncover the interaction and behavior of factors involved in a conflict multidimensional process and to facilitate the monitoring and the management of conflicts that can promote the national unity and the regional integration, stabilize the African continent and boost the socioeconomic and political development. In this dissertation, we use quantitative data from a secondary source named SCAD (Social Conflict Analysis Database). SCAD contains conflict events such as protests, riots, strikes, inter-communal conflict, government violence against civilians, and other forms of social conflicts reported on 48 African countries from 1990 to 2017. In our multivariate analysis, we found first that there is a strong association between conflict event and conflict issue. Second, there is a significant association between conflict escalation and repression. Third, the average number of ethnic and discrimination issues in former French colonies is higher than the average number of ethnic and discrimination issues in former Britain colonies. Our statistical approach helps to classify predictor variables according to their interrelation and to predict the number of conflicts in Africa. Results in this dissertation may be useful in reducing conflicts in Africa and advance the cause of humanity and of science.
dc.description.tableofcontentsChi Square Test of Independence -- Clustering Analysis -- Principal Component Analysis (PCA) -- Multi Linear Regression
dc.format.extentxi, 88 pages
dc.identifier.urihttps://hdl.handle.net/10355/75783
dc.subject.lcshConflict management -- Africa
dc.subject.lcshWar -- Africa -- Causes
dc.subject.otherDissertation -- University of Missouri--Kansas City -- Mathematics
dc.titleApplications of multivariate analysis to understand the dynamics of African conflicts
thesis.degree.disciplineMathematics (UMKC)
thesis.degree.disciplineSocial Sciences (UMKC)
thesis.degree.grantorUniversity of Missouri--Kansas City
thesis.degree.levelDoctoral
thesis.degree.namePh.D. (Doctor of Philosophy)


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