Essay on Stats: Poverty and Life Expectancy

Submitted By bea0491
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Pages: 5
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During this project our team compared and analyzed two sets of data: the average life expectancy and the per capita GDP of a group of countries. We used excel commands to organized all of our given data, and to find the relationship between the GDP and the Life expectancy of the countries, we also did some research to find out what the GDP per capita and life expectancy of a country meant. Before starting this project our hypothesis was that Individuals born in wealthier countries, can expect to live longer than those born in poor countries.
The correlation between GDP per capita of a country and their Life expectancy is r= 0.575763 which means that there is a strong positive relationship between these two sets of data. We believe that our results were what we were expecting them to be and our hypothesis was right because countries with less poverty have a higher life expectancy. We found out by looking at our data (frequency distributions, scatterplots, histograms, mean and standard deviation) that it is not the aggregate growth in income, however, that matters most, but the reduction in poverty. We also how the connection between per capita GDP and life expectancy weakens after reaching a certain level, this is because people consume needs in order to survive, but once a person’s needs are met, the rest of their money gets spend on non-necessities like going to movies, buying a TV , paying for a phone etc.. If everyone’s needs are satisfied, then any increase in GDP per capita would barely affect life expectancy.
GDP stands for Gross Domestic Product. GDP is the total monetary value of a country’s produced goods over a certain amount of time. It is used to determine a country’s wealth in terms of the economy. Per capita translates in Latin as “by head”, so it is translated as “per person”. Per capita GDP is a measure of GDP divided by the population of a country. Taking the country of Brazil as an example, Brazil’s per capita GDP is $11,640 with an average life expectancy of 74 years. It may make more sense to use per Capita GDP rather than the overall GDP because each country has a different population, and in each country not everyone has the same amount of income. Some people may of a low-income household or even poor, while others may be of a higher-income household and really wealthy that’s why GDP normally increases as the population increase, while GDP per capita may decrease when population increases. So, using overall GDP may not be the best way to look at a country. GDP per capita and life expectancy of a country are parameters because they count the whole population rather than just a small sample however GDP per capita is not a totally accurate way of measuring a countries wealth either because it is based on the average combined wealth of the entire country divided by the whole population, and lots of countries have extremely rich people that can tip the average a bit higher. It can work the same with life expectancy, it could be for example in the Democratic Republic Congo they have diamond minds which create large amounts of wealth, however most of the population is poor and must work in the diamond mines, this is a dangerous job which brings down the average of the life expectancy however the average is probably still artificially high because of the local mine owners/management that doesn’t have to do the dangerous mining work.
In conclusion after computing and analyzing our data we concluded that GDP does affect the life expectancy of a country and that wealthier countries usually do live longer than poorer countries, however there are many factors that affect this two measurements like, social, geographic and the distribution of wealth among the habitants of a country, which makes them not totally accurate. We really like working on this project because we were able to use what we learned during this course and apply it to a real life problem.

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