The following blog post contains three constructed bar graphs. Of these are comparisons within the following categories: technology, age, and religion. Each graph takes information from an in class completed worksheet I did. Additionally, these numbers are combined with actual accurate global data, and the averages of my class peers worksheets. The requirement is that among each category, students predict how many people are members of a subcategory from a pool of one hundred. From this we have the World of 100. In the case of age, a division of how many people out of one-hundred are in either one of three age groups: 0-14, 15-64, and 65+. The rest of this post will be composed of my reflection on the difference between data sets. Additionally, each graph will receive a critique.
- Technology in a world of 100: My predictions in comparison to the class average were all but one time closer to the the actual statistic. I noticed that my previous readings about the lifestyle of many impoverished people in places outside of the United States had informed me well about the widely available use of cell phones. With a prediction of 67 people having cell phones, I was off by 8 individuals. In actuality, even more people in a world of 100 are cell phone subscribers. In the other two subcategories, my numbers were not as close. Considering that the internet is reaching further than in previous years, I assumed a larger number of internet users. In particular, the one-laptop-per-student program that combats global education issues has grown extensively. On the train of this thought, I figured there were more people able to connect to the World Wide Web by either owning a reduced price computer, or sharing one. This correlates into my incorrect predictions of more people owning computers than in actuality. Although I assumed 60 people would be without a computer realistically it is is set at 78. In reflection, access to infrastructure like wires and other telecommunication materials would be a costly endeavor for many countries. Also, the cost of a laptop or its cultural worth may not be as prominent in the lives of others who live within different daily circumstances. Overall, it was pleasing to see a large comparison of technology that currently unites people across great distances and remotely near one another.
- Age in a world of 100: Looking at the bar graph I developed using my predictions, the class average, and the actual statistics, I noticed a clear relationship to the common 'bell curve'. This appears in statistics to show averages, often seen in grades, it is most common in life expectancy in relationship to time. When I was completing the worksheet in class, I did not use this knowledge to better my predictions consciously. However, my statement of there being 65 people between the ages of 15-64 was only 1 away from the actual number of 66. This number makes sense probabilistically, considering that there would be at least one person for each age. Then if you assume that globally most people have a shorter life expectancy, the remaining slots in prediction can be divided with an emphasis in the youngest group of 0-14. However, I seemed to have an optimistic outlook on the longevity of a human life. With not much left to compare, it was expected by the class that there would be many people living in the 0-14 and 65+ groups. I think this was because of the increased practices within modern medicine, and population growth. However, I believe the population of the world is more heavily controlled by the middle group were people are in their middle days of life.
- Religion in a world of 100: Among the graphs I have posted, my predictions in regards to religion, these numbers clearly represent an inaccurate interpretation of the different religions practiced around the world. When completing this part of the worksheet, I very bluntly assumed I would need to account for what I considered to be a major religion missing from the categories, Judaism. Perhaps, the real error in my predictions was assigning the majority of people to the "other religions" sub-category. In doing this, it felt like a wild card option. By this I mean, well of the other religions maybe a few are Christians, Jews, or Muslims. Looking back, I should have erased my distribution of 30 people belonging to other religions. However, I decided that I would not erase any initial thoughts I had during my worksheet completion. Thus, in hindsight I did not make an informed decision about the number of people belonging to a particular religion. Certainly, I would have assumed Christianity was the most widely held faith internationally. However, I assumed that the Middle-East/India/Asia would account for the majority of members in my population of 100. From this I made the decision to put my second largest division of people into the sub-category of "Hindu". Interestingly, this was the closest prediction I made among the many others. All of my other predictions were significantly bound to a margin of incorrectness. In refection, I wish I had utilized the labeled religions more effectively, and been aware of the number of people that do not claim a religion.
Looking through other answers I completed on my worksheet, I was most inaccurate in the Drinking Water category. A week of service in the DR (Dominican Republic) convinced me sternly of the impoverishment of water available around the water. 97% of Earth's water is salt water. This leaves only 3% freshwater. I then distributed 3% around the world; water which is drinkable. Accounting for water privatization, I assumed that only 30 people in a world of 100 would have water. The other 70 would have unsafe water. Well, this category calls for a lot of analysis and reflection. The question was not, "How many people do not have water?" Instead, the sheet asked of the 100 people, how many of them in fact had safe drinking water. Even with this clarification, I still would assume that the number would not be the correct 87 people living with access to safe water. The secret in this statistic is 'access'. There could be a group of people living in Zambia that have safe drinking water. However, consider that this safe drinking water is only accessible at a pump two hours away. Families of the world may have access to safe drinking water, but I hope for a future where 100 out of 100 have clean water, not just access. In conclusion, there are 13 people that use 'unimproved water'. Additionally, there are varying degrees of improved in relationship to disease.
Another category where I was surprisingly incorrect was the number of people living on less than 2USD per day. I predicted that 86 people would be living on less than 2USD a day. The real number was 48. Some people in class talked about how the world really was not as bad as people view it to be. However, I feel there is a lose of emotional understanding to these numbers. A person could make 2.50USD a day. Maybe they will make 5USD a day. However, when you account for different elements, there is the factor of the labour involved in the job to obtain the wage; more interesting is the life expectancy contract with the number of years a person will work in their life. With my guess of only 14 people living on more than 2USD per day, I was missing 38 people. After this worksheet, I am interested in developing a keen-global lens to view in understanding our world - of billions.