Day 146: Gapminder in Stats!
I was so excited to finally incorporate Gapminder into my AP Statistics class today! In December, I had the privilege to observe one of my social studies colleagues as she used Gapminder with her seniors to explore social trends. The students then used Gapminder to explore their own hypotheses around a social trend. Afterwards, we talked about how she planned and prepped her students to use the site independently.
Fast forward to now. I noticed that one of the alternative examples for our textbook referenced variables in gapminder, and I said to myself, “Self, its time to dip our toe into using Gapminder in class.” Here is the problem:
What does a country’s income per person (measured in gross domestic product per person, adjusted for purchasing power) say about the under-5 child mortality rate (per 1000 live births) in that country? Here are the data for a random sample of 14 countries in 2009 (data from www.gapminder.org).
Prior to class, I played with the site, selecting the 14 countries used in the example. Then I figured out how to get it to 2009 (obviously, to some, the time line at the bottom). I also found out how to “hide” the other countries to then be able to see the sample fourteen using the opacity toggle. We looked at the entire population of data and noticed that the relationship was definitely NOT linear. We then looked at the selected 14 countries, but the graphic seemed cluttered with the names and it was hard to see that relationship still was curved.
So I created an Nspire document with the data included so we could look at the data without the labels. This also gave the opportunity to try the reciprocal function idea on the data and see if it straightened (linearized) it.
We went through the usual discussion of the power transformation of data (and some even wanted to know why it worked). And we then compared to what happens in Gapminder when the log scale is used on both axes. Fun to see the connections!
The last part of the discussion was around what the inputs and outputs of the regression equation are, using the question below. Didn’t quite finish, so we will need to use some time on Monday to solidify concepts and fine-tune the process. But all in all, an okay lesson.
I would like the students to actually do the creating of the graphs on Gapminder and determine how to transform, but I have to remind myself that is not the purpose of this class. And with the AP exam in just a few weeks, I have to pick the most impactful experiences. Maybe this could be a great end-of-year project for one of my students. What do you think?