Channels, Fall 2017

Page 88 Beck, Diza, Searl • Bridges and Bandits number and significance between the Inflows of Asylum Seekers and Terrorism Incidents. A description of the p value, degrees of freedom, critical value for a one-tailed test, r , and coefficient of determination are included in order to help highlight key facts that would be needed in order to draw conclusions from the statistics run. The last set of statistics run for countries was a linear regression for those countries where there was a very strong linear correlation between inflows of asylum seekers and terrorism incidents. Appropriate tables are included below in the “Results” section of our study. For example, the ANOVA test was run and the F-test was examined in order to see if the null hypothesis would need to be rejected. Also included is the predicted number of terrorism incidents for countries if the number of asylum inflows was to increase markedly. There is also an indication of the mean number of terrorism incidents within a 95% confidence and prediction interval. Lastly, an examination of the percent of asylum seekers in each of our six countries that were coming from terror-prone countries was made. There was a tool in the International Migration Database that allows for one to control the statistics for the country of birth or nationality of asylum seekers. Based on the Global Terrorism Index, the number of asylum seekers from the top 5 countries with the highest impact of terrorism (Iraq, Afghanistan, Nigeria, Pakistan, and Syria) was examined in regard to their proportion of the total asylum seekers in each of our six selected countries. The results from this in-depth study of a certain variable are visually displayed in line graphs. Results Germany The following two graphs compare the inflow of asylum seekers (on the left) with incidents of terrorism (on the right) in Germany. The general trend of both lines shows an increase after 2013, which indicates a potential correlation between both variables.