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Visualizing sampling error and dynamic graphics

Robert Grant writes:

What do you think of this visualisation from the NYT [in an article by Neil Irwin and Kevin Quealy but I’m not sure if they’re the designers of the visualization]? I’m pretty impressed as a method of showing sampling error to a general audience!

I agree.

P.S. In related news, Antony Unwin writes:

A couple of weeks ago you had a discussion on graphics on your blog and it seemed to me that people had very different ideas about what the term “Interactive Graphics” means. For some it is about interacting with presentation graphics on the web, for others it is about using interactive graphics to do data analysis. You really need to see interactive graphics in action to get a feel for it.

I have made a ten minute film to give the flavour of interactive graphics for data analysis with data on last year’s Tour de France and using Martin Theus’s software Mondrian.


  1. John Mashey says:

    My Yorkshire wife has been watching the Tour de France today …

    The Tour de France interactive graphics video was good.
    EDA is good, but I may be biased, I still have Tukey’s EDA book. :-)

  2. I’d go further. I think the NYT graphic is brilliant for two reasons.

    First, it’s an awesome illustration of sampling variability. Second, and perhaps more importantly, it’s an illustration of our tendency to try to read meaning and trend into noise.

    Jim Albert hits both points in his fantastic book on baseball stats, Curve Ball. Albert’s book pened my eyes to statistical thinking. What’s amazing is that there’s not even much algebra in the book. Albert starts with a disucssion of All-Star Baseball, a spinner-based simulation game, to illustrate the variability of what a season (500 draws or so) might look for someone with a 3/10 chance of getting a hit per at bat.

    Albert also discusses the tendencies of sports fans to describe players as slumping or streaking based on what’s just noise. Then he builds up to some neat analyses of streakiness (what a statistician might call non-stationarity) and how to detect it.

  3. Dale says:

    I looked at Jolicharts and could almost see it as a violation of principles of good display. Sure the web presentation is slick, but the graphics are fairly standard and many of the examples are superimposed over chartjunk. I guess that appeals to people since it looks entertaining, but virtually all of those examples distract from the real data. And, I love the bold claims on the website about how this will revolutionize business intelligence. Maybe its just me, but I don’t see the revolution in this.

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