• Misleading Map of Buffalo Snow

    September 27, 2007  |  Mapping, Mistaken Data

    Buffalo Snowfall Map Without LegendI saw this map of the average snow levels in Buffalo. I think I just glanced at it and that was about it. When you first look at the map, what do you make of the colors? When I see green for snow levels, I think no snow. Am I crazy? What do you think?

    So the image was kind of in my head all this summer while I was in NYC. When I told people that I was going back to Buffalo after my internship, they always gave this look that said, "Ha, have fun during the winter," and then they would actually say it and then go into how they measure the snow level by comparing it against a giant pole.
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  • Finding Weirdness in Temperature Data

    July 9, 2007  |  Mistaken Data

    wunderplot500

    After parsing Weather Underground pages to grab temperature data, it's time to look at the data. Can't download all that data and not do anything with it!

    First off, in my initial pass of my parsing script, I accidentally cut the month range short, so I didn't get any data for December from 1980 to 2005. It should be noted that these plots don't show this missing data. Um, there's no axes or labels either. Sorry, I got a little lazy, but that's not the point now anyways.
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  • Juice TESTING in Competitive Sports

    July 8, 2007  |  Mistaken Data

    Juice testing

    It's easy to see how Statistics got this bad wrap because it's so easy to lie with data, charts, and graphs. Sometimes it's on purpose -- someone might try to present "good" results that actually suck. Sometimes it's accidental -- someone might have misread or didn't read the documentation that came with the data. In the case of Swivel's most recently featured graph, it was the latter. A case of mistaken identity so to speak.

    The data about doping tests in sports came from here. Now the graph on Swivel would have you believe that the data represent the number of doping cases found in each sports; however, according to the USADA report, the data is actually the number of tests the association conducted inside and outside competition during the first quarter of this year. The report contains no data on the USADA's findings.

    What We Learn

    What can we learn from this? It's great to visualize data, but you have to be careful. Read the documentation. Find out what the data is about, because without context, the visualization or any findings are practically useless. Statistics isn't to lie. In fact, it's the exact opposite. Statistics came about and exists today to reveal the truth.

Unless otherwise noted, graphics and words by me are licensed under Creative Commons BY-NC. Contact original authors for everything else.