DATA150-HD

The data I decided to take a closer look at was literacy rate vs income in India and Italy over the past 40 years up to 2010. Since 1980 India’s income and life expectancy have increased but seems to now be leveling out. This is surprising because there is still so much room for them to improve. Italy has also increased in literacy rate and income but only ever so slightly. The improvements in Italy’s literacy were minute while the improvements in India were more obvious going from a 40% literacy rate to almost 70%. Italy was already nearing 100% literacy in the 1980s. The income increased from about 1,400 to 4,400. Italy’s income went from about 28k to 43k which is a large jump but doest seem as significant compared to India because of the initial numbers already being so large. India had a higher rate of change in their literacy and Italy had a higher rate of change in their income. I honestly expected to see a much more obvious linear effect with literacy rate and income. In the United States most people figure the smartest individuals make the most money. Hence students paying thousands of dollars to go to college in hopes of landing a good job. However, it seems that literacy rates have grown much quicker with income barely trailing. I would attribute this to knowledge becoming more widespread because of technology, but jobs becoming harder to find with increasing population and economic hardships. It is also surprising to see how many countries still are under levels of 80% literacy in adults including India. Italy had higher literacy rates in the 80s than India does currently. The differences in India and Italy are most likely attributed to the different levels of development. Though India has rich cities with wide development it also has vast populations of underprivileged and underdeveloped. This is why in the first Ted Talk we watched, Rosling mentioned having to be more specific and realizing that some places like in Africa can have some of the richest cities as well as the poorest. This is why using data science to target the in need people of larger areas like Blumenstock talked about would be so useful.