values for the indicators are some years and have not been updated to correctly represent current events. One limitation which could have made the results inaccurate is the fact that it is easier to acquire data for those countries that are more developed, are not involved in wars, and are more politically stable. This means that the information gathered about them is more complete than that of countries like North Korea, which have limited access to data and surveys, or those in Sub-Saharan Africa, which are in constant disputes and chaos. This can generate misleading results and conclusions about quality of life and refugee numbers in politically unstable and less developed countries. There was also an indicator which had questionable data. Population density was displayed, like all other indicators, as a gradient of colors. Most countries were ranked the same number, meaning they had relatively similar ranges of population density, which made the map mostly one specific shade of the color. It was difficult to believe that the US and China were ranked equally, considering the great difference in population. One theory to explain this is that the area used to calculate population density also includes uninhabitable areas, such as mountain ranges or deserts, skewing the data. It was also a challenge to determine which indicators were suitable to calculate the quality of life in countries. Not all indicators were suitable for this calculation, hence why GDP was discarded from the initial list. Military expenditure, for example, was complicated to work with since initially, it was intended to illustrate military activity and political unrest, yet in reality many countries invest highly on defense and are not involved in warfare, so determining whether high military expenditure was a positive or negative feature was difficult. One last challenge faced in the project was displaying the data. While showing the composite rank for the countries was straightforward and easy to visualize, refugee data was a little more difficult to display. For instance, the placement of the points was calculated by creating a square around the full area of the country and placing it in the middle, so in the case of the United States, the
values for the indicators are some years and have not been updated to correctly represent current events. One limitation which could have made the results inaccurate is the fact that it is easier to acquire data for those countries that are more developed, are not involved in wars, and are more politically stable. This means that the information gathered about them is more complete than that of countries like North Korea, which have limited access to data and surveys, or those in Sub-Saharan Africa, which are in constant disputes and chaos. This can generate misleading results and conclusions about quality of life and refugee numbers in politically unstable and less developed countries. There was also an indicator which had questionable data. Population density was displayed, like all other indicators, as a gradient of colors. Most countries were ranked the same number, meaning they had relatively similar ranges of population density, which made the map mostly one specific shade of the color. It was difficult to believe that the US and China were ranked equally, considering the great difference in population. One theory to explain this is that the area used to calculate population density also includes uninhabitable areas, such as mountain ranges or deserts, skewing the data. It was also a challenge to determine which indicators were suitable to calculate the quality of life in countries. Not all indicators were suitable for this calculation, hence why GDP was discarded from the initial list. Military expenditure, for example, was complicated to work with since initially, it was intended to illustrate military activity and political unrest, yet in reality many countries invest highly on defense and are not involved in warfare, so determining whether high military expenditure was a positive or negative feature was difficult. One last challenge faced in the project was displaying the data. While showing the composite rank for the countries was straightforward and easy to visualize, refugee data was a little more difficult to display. For instance, the placement of the points was calculated by creating a square around the full area of the country and placing it in the middle, so in the case of the United States, the
gr3pap.docx