Quality: About This Data Set
Urban life expectancy on the decline
In order to better understand my data from a wide view, I created Stem Plots for the three main data comparisons that helped to answer my question: Male compared to Female; White Male compared to Black Male; White Female compared to Black Female.
From creating these visualizations, I could easily compare where some of my data compared and where there were some holes. There aren't values for black male and female life expectancy in Indiana county. However, this makes sense given the data because African American populations in rural areas is quite low compared to urban areas.
One way I could have combatted this error, was to plan ahead and research rural counties with a higher African American population so there wouldn't be null data. Or compare every county in Pennsylvania so my data set would be large enough to get a wider view and generalize rural and urban areas of the state.
I hypothesized that life expectancy in rural counties would be higher than in urban counties. This hypothesis was proven true. The results are shown in the bar charts below.
There weren't any outliers in my data, but this is most likely because the ages are averages. Therefore, the outliers were already dealt with when compiling the data. The patterns are normal, but I find it interesting that there isn't a wide range of ages. Most people (regardless of gender or race)live to be an age with a small standard deviation from each other year after year.
The lack of completeness is apparent in the bottom two graphs. However, as mentioned earlier, this makes sense and fits the data set given rural populations.
Although my hypothesis was proven true, the life expectancy difference was much closer than I expected. Rural area residents only live about a year longer than urban residents. I decided to do some more research in this area to prove if this small discrepancy was correct.
According the Center for Advancing Health people in urban environments have had an increasing life expectancy rate, while those in urban areas have had a decreasing life expectancy rate. They attributed 70 percent of the gap in life expectancy can be attributed to higher rates of accidents, cardiovascular disease, COPD and lung cancer in rural residents.
Associate director of the UCLA Center for Health Policy Research, Steven P. Wallace, Ph.D., found that people who live in rural areas have a lot of the same challenges as inner city people. 'These include safety, getting enough physical activity and even getting good nutrition—in spite of all the food growing around many of them—the more rural the location, the more difficult it often is. Additionally, young adults have migrated from rural farming areas, leaving people with the lowest incomes and the least opportunity—both factors correlate strongly with life expectancy.'