Monday, April 18, 2011

Gapminder - Education Statistics

I spent a few minutes today playing around with Gapminder World to see if the data they had could show anything interesting regarding education. Perhaps such a powerful infographic/data visualization tool could show us clearly what factors have definitive correlations between math and literacy rates. I wish they had statistics that measured how happy people are, or data that showed the breadth of study (i.e. how many of them had access to art, music, theater, culinary arts, philosophy, or other classes). But, I'll have to do with what has been measured, which by-the-way is an interesting set of data in itself. What gets measured is a direct indicator of the values of those collecting data. This act in itself contains an important bias. It means that the values of those who do not put much faith in data and statistics are always under-represented in data and statistics. Therefore, naturally data and statistics will more likely support the values of the "data-driven" rather than those who are not.

That said, here are some of the more interesting data sets I found:

What was interesting about this graph was when you animate it there doesn't appear to be any correlation between GDP/capita and math achievement in 1995 but as time goes on over the 12 years of the data set all data sets come to convergence upon an emerging diagonal line indicating that the world is trending toward income being an indicator of math achievement level but perhaps it didn't used to be.

Another place where GDP/capita appears to have a direct correlation is with adult literacy rates as shown here:

But, the correlation is not nearly as strong when it comes to those only between the ages of 15 and 24. Odd. I wonder why this is.

While the GDP/capita data seems to show a strong correlation on math achievement and literacy rates, what seems to be a stronger indicator is fertility rates. Gapminder clearly shows an inverse relationship between math proficiency & adult literacy and the number of children per family.

When it comes to wealth distribution the results are less clear. Gapminder has many different data sets that could be used to draw this comparison but none of them are absolutely conclusive. By looking at who the outliers are in these it seems how nations acquire the majority of their wealth matters as much as how it is distributed. It seems like we could derive from these statistics that the more stable and sustainable the nation's wealth combined with how evenly distributed it is determines the level of math achievement and adult literacy.

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