The Importance of Collecting (and Reporting) Good Data

Image capture from Ben Wellington's TED Talk on what can be done with data from New York City.
Image capture from Ben Wellington’s TED Talk on what can be done with New York City’s data.

I’m having my students collect all sorts of data for Chicken Middle, their student-run-business. Things like the number of eggs collected per day and the actual items purchased at the concession stand (so we don’t have to wait until we run out of snacks). It takes a little explanation to convince them that it’s important and worth doing (although I suspect they usually just give in so that I stop harassing them about). So this talk by Ben Wellington is well timed. It not goes into what can be done with data analysis, but also how hard it is to get the data in a format that can be analyzed.

Doubly fortunately, Ms. Furhman just approached me about using the Chicken Middle data in her pre-Algebra class’ chapter on statistics.

We’re also starting to do quarterly reports, so during this next quarter we’ll begin to see a lot of the fruits of our data-collecting labors.

How to Make Good/Useful Graphics

Flowing Data has a nice post that gets at how to make good images of data. It’s called, “5 misconceptions about visualization“.

The misconceptions:

  • Visualization is for making data flashy
  • Software does everything
  • The more information on a single graphic, the better
  • Visualization is too biased to be useful
  • [A Visualization] has to be exact

The Power of Graphs

A couple days ago I had students present their physics lab reports to the class. They did a good job, but I think I need to emphasize the importance of including graphs in their results. It’s much harder to look for trends and patterns in the data without charts, especially when presenting to an audience.

An interesting political science study (via Yglesias) found that it’s much easier to change people’s minds when you show them graphs, even when people don’t want to believe what you’re telling them.

[P]eople cling to false beliefs in part because giving them up would threaten their sense of self. Graphical corrections are … found to successfully reduce incorrect beliefs among potentially resistant subjects and to perform better than an equivalent textual correction.

–Nyhan and Reifler (2011): Opening the Political Mind? The effects of self-affirmation and graphical information on factual misperceptions

Despite the fact that the number of jobs increased in the last year (according to the Bureau of Labor Statistics), many people who disapprove of President Obama believe that the economy lost jobs. A lot of people who were told this with text still believed that there was a net job loss, but when presented with a graph of the actual data the number decreases to close to zero. (Graph from Nyhan and Reifler (2011)

Teachers know how hard it can be to correct misconceptions – people tend to stick with the first thing they learned – so it’s good to see that graphical corrections can make a big difference.

Fortunately, my physics students are changing over to math next week, so we’ll be able to use their experimental data to draw lines, find gradients and do all sorts of interesting things.

What’s Needed for a Nation’s Peace

The Fund for Peace has been doing a lot of thinking about what it takes for a country to be considered peaceful, and what it takes for a state to fail. For the last seven years they’ve been putting together maps of the world with an index of how stable different countries are.

Finland - the most sustainable state, at least according to the Failed State Index.

While it’s pretty in-depth and makes for rather sobering reading, it’s worth taking a look at the criteria they’ve come up with to determine a country’s stability. It may be useful to include some of this information in the cycle where we focus on peace.

Their criteria for instability include:

  • Demographic pressure (such as having too many young adults, as we’ve seen in Egypt)
  • Amount of refugees and internally displaced peoples (refugees are people who’ve crossed international borders). Both leaving or entering refugees can undermine stability.
  • Historical Injustice – communities can have an understandably hard time forgetting the past, just look at Isreal/Palestine.
  • Brain Drain – when countries start to fail, the first to leave are the ones who can afford to. Yet these intellectuals and professionals, with their college degree are vital for creating a stable and prosperous country.
  • Inequality – especially when driven by active discrimination (wealth inequality is something to watch out for).
  • Economic decline – pushes trade into the black market and increases criminality and corruption.
  • Illegitimacy of the state – if people don’t believe the people in government have everyone in the country’s best interests at heart, and are only looking out for themselves and their friends, then there’s probably going to be trouble.
  • Public Services go kaput – It’s a really bad sign when the government can meet people’s basic needs – like picking up the garbage.
  • The Rule of Law goes kaput – when you’re ruled by the caprice of men, and your rights under the law are not respected, you may begin to consider and agitate for other options for government.
  • Personal Armies – forces that are tied to individual leaders, like private militias or super-secret police for example, are very damaging to a country’s cohesion.
  • Fighting elites – healthy countries need robust arguments in their political class – think checks and balances – but it can go too far and lead to things like extreme nationalism and ethnic cleansing.
  • Invasion – both overt invasion and covert meddling in the affairs of a country are unhealthy for that state’s stability.

It’s also very nice that you can download their index data as a MS Excel spreadsheet, which you can let students analyze to answer their own research questions. For example, I was wondering what was the difference between the best, the worst and the USA, so I plotted this graph.

Comparing the best (Finland), worst (Somalia) and the USA using the Fund for Peace's Failed State Indicies.

The USA is much closer to Finland than Somalia, thank goodness, but should probably watch out for that Uneven Development (wealth inequality).

I think something like this would make a good experiential exercise for the science of geography.

U.S. Immigration Data

Raymond Cohn has a great table of immigration data on the Economic History Association website.

This data ties very nicely into the work we’re doing on graphing. The Excel file with the post 1820 data, and another with pre-1790 data, make it easier to work with (note the pre-1970 data comes from the Wikipedia page on the history of immigration; it was the easiest source to find a table of data).

Since each small group of students is responsible for a different wave of immigration, the groups will create bar graphs showing the countries of origin for each wave. They should look like these:

U.S. Immigration from 1820 to 1831. Data from Cohn (2010).

and,

U.S. Immigration from 1900 to 1914. Data from Cohn (2010).

Plotting the time series as a line graph would be another great way to slice the data:

Comparison of U.S. Immigration Rates from Great Britain and Central Europe. Data from Cohn (2010).

Note that the data in the table is as a percentage of total immigration, so the numbers do not compare directly from one time period to the next; however, the proportions still work to show the same patterns.