Statistical Insights and Association Mining for Terrorist Attacks in Egypt

Abstract

Terrorist attacks are the most significant challenging issue for the humankind across the world, which need the whole attention of all nations. No doubt, that the terrorism attacks in Egypt negatively affect its economy and decreases its opportunities for foreign investments in the last decade. In this paper, statistical techniques will be applied to terrorism attacks occurred in Egypt in the last four decades. The used database in this study is the Global Terrorism Database (GTD), which is published by the University of Maryland. Statistical insights graphs will be presented in the paper. In addition, association-mining algorithms will be used to find the frequent hidden patterns in the database. Those algorithms help in generating composite rules by mining the database, which generates deeper meaningful insights. The statistical insights and association mining will help to understand the nature of terrorist attacks in Egypt. Moreover, it will give the decision-makers the knowledge to overcome and step ahead the terrorist attacks before occurring. This will reflect on Egypt economy positively and increases the opportunities to have better investments and encourage the return of tourism.