My 15 year-old daughter Grace got fired up by Hans Rosling’s first Ted talk.  She took up the challenge of learning a little bit of R code to build a web display using Google’s Motion Chart for her final European History project, June 2015.  Her project display involves time series of population, infant mortality, and per capita GDP for nine countries, 1820-1992.

This was a real data analysis problem. For Grace, most of the work involved gathering the data, getting it into the right format for display and thinking about  the data limitations. As she worked to understand the meaning of the numbers, I got to trot out Lord Kelvin’s advice, "the more you understand what is wrong with a figure, the more valuable that figure becomes.“

I showed Grace how to insert the R code into a Shiny app and then open a shinyapps.io account to share with her class.  (Here’s the link for her project.)


The overall pattern is decline in infant mortality and increase in wealth from the start of each country’s series through 1992.

Interact with the display for individual countries and you can see the impact of World Wars, the Great Depression and the break up of the Soviet Union.   For example, the Netherlands experienced a sharp drop in estimated income and increase in infant mortality at the end of World War II.



Technical Notes
Grace used population and constant dollar GDP per capita data from the Madison historical series.

Infant mortality series--deaths before age 1 per 1000 live births--came from a physical book, International Historical Statistics: Europe 1750-1993 (4th edition, 1998) by B.R. Mitchell, London: Macmillan Reference; New York, N.Y.: Stockton Press, accessed at the University of Wisconsin-Madison research library. That source meant a bit of time reading and typing numbers into a spreadsheet, a throwback to 20th century data analysis.

We found that the Google chart element sometimes loads slowly--be patient and if you run out of patience, hit the reload button.   Since the Motion Chart is rendered in Flash, you can use the free browser download from Puffin if you want to see the chart on an iOS device.

Grace allowed me to share her code, I have posted it here on GitHub.

Super User

David Leonhardt in today's New York Times invites readers to play a little game--guess a rule for a sequence of three numbers.  Here's the link.  

Invented by psychologist Peter Cathart in 1960 ("On the failure to eliminate hypotheses in a conceptual task", Quarterly Journal of Experimental Psychology, 12, 3, 129-140, link here), I first learned the game from my colleague Jerry Langley in 2001.  Jerry uses it to teach people about the importance of testing ideas and predicting outcomes, as motivation for learning the Model for Improvement.

Leonhardt usefully discusses the game in the original context of "confirmation bias"-there seems to be a natural human tendency to seek confirmation of views we already have and to avoid disconfirmations.

The upside of the bias is that we're sometimes right and a quick confirmation is all we need to make progress.  The downside of the bias is there are few if any universal rules related to human systems so at some point our mental model will fail.   If we never determine situations where our views fail, we're quite constrained in our ability to learn and develop systems that do work, in the appropriate circumstances.

Leonhardt's conclusion:

"When you seek to disprove your idea, you sometimes end up proving it — and other times you can save yourself from making a big mistake. But you need to start by being willing to hear no. And even if you think that you are right, you need to make sure you’re asking questions that might actually produce an answer of no. If you still need to work on this trait, don’t worry: You’re only human."



I’ve been working with colleagues at the Institute for Healthcare Improvement for the past two years to help healthcare organizations get “Conversation Ready”—to be ready to engage with their patients and clients about end of life care wishes, to be good stewards of that information and to use that information wisely.

The idea is that as more and more people are having The Conversation about end of life wishes, as promoted by The Conversation Project and other initiatives, healthcare organizations need to be prepared with educated staff and effective information systems to respond effectively.

My primary job on the project has been to lead the work on measures, to answer the second question of the Model for Improvement:  How will we know that a change is an improvement?

The measures help guide the tests the organizations have deployed as they learn effective ways to educate themselves and organize work processes and information systems. Our interim report on what we’ve learned has just been published as an IHI White paper, available on the IHI website.

My faculty colleagues and the Conversation Ready organization teams have applied their hearts and minds to caring for people and their loved ones at end of life.

I know I have learned more from them than they have learned from me.

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