Blog Archives

Statbusters are back, taking on robots that hire people

July 27, 2015
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In our newest column, we take on the recent media obsession with companies who make robots that hire people. (link) As with most articles about data science, the journalists failed to dig up any evidence that these robots work, other than glowing quotes from the people who are selling these robots. We point out a number of challenges that such algorithms must overcome in order to generate proper predictions. We…

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Deja vu! Doping accusations at Tour de France

July 24, 2015
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Deja vu! Doping accusations at Tour de France

Gabe Murray wrote to Andrew Gelman, asking for comments about the accusations hurled at the current Tour de France front-runner Chris Froome. He said: This post by VeloClinic has been getting a lot of media attention in the past few days, within the context of Chris Froome's dominant performance in the Tour de France: http://veloclinic.com/estimating-the-probability-of-doping-as-a-function-of-power/ The assumptions seem very dubious to me, and I would love to see a critique…

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I try hard to not hate all hover-overs. Here is one I love

July 23, 2015
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I try hard to not hate all hover-overs. Here is one I love

One of the smart things Noah (at WNYC) showed to my class was his NFL fan map, based on Facebook data. This is the "home" of the visualization: The fun starts by clicking around. Here are the Green Bay fans...

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Statistically significant. What does it mean?

July 22, 2015
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Andrew Gelman has a great post about the concept of statistical significance, starting with a published definition by the Department of Health that is technically wrong on many levels. (link) Statistical significance is one of the most important concepts in statistics. In recent years, there is a vocal group who claims this idea is misguided and/or useless. But what they are angry about is the use (and frequently, mis-use) of…

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United Nations gets dataviz

July 21, 2015
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The UN, as I noted before, is getting into the dataviz game. Here is an announcement about a Data Viz Challenge that has just started. Flood them with ideas! *** I am writing to invite you and your network of...

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It is possible to not learn real causes from some A/B tests

July 20, 2015
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It is conventional wisdom that A/B testing (or in proper terms, randomized controlled experiments) is the gold standard for causal analysis, meaning if you run an A/B test, you know what caused an effect. In practice, this is not always true. Sometimes, the A/B test only provides a statistical understanding of causes but not an average Joe's understanding. Let's start with a hypothetical example in which both definitions are aligned.…

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Incomprehensible, and even insidious

July 17, 2015
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Incomprehensible, and even insidious

A reader Alex V. nominated this chart as one of the most incomprehensible ever: This comes from the Annual Report 2014 of Allison Transmission. I applaud the fact that they obviously spent time making the charts. This is not something...

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Maps and legends

July 15, 2015
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Maps and legends

This chart, which I found flipping through Stern magazine in Germany, accomplishes one important goal. It makes me stop flipping, and look. The chart presents a point of view that is refreshing. The Airbus A320 is a true collaborative effort....

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Flawed thinking about causes

July 13, 2015
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One of the most misguided and dangerous ideas floated around by a group of Big Data enthusiasts is the notion that it is not important to understand why something happens, just because "we have a boatload of data". This is one of the central arguments in the bestseller Big Data, and it reached the mainstream much earlier when Chris Anderson, then chief editor of Wired, published his flamboyantly-titled op-ed proclaiming…

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What is an interaction effect?

July 9, 2015
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What is an interaction effect?

One statistical concept that instructors frequently don't have time to cover in Stat 101 is the "interaction" effect. I will explain this concept using the fantastic interactive graphic by the visualization team at the German publication Zeit (please also read the corresponding post on Junk Charts here for some background.) When we ignore interactions, we end up with overly simplistic statistical summaries. For example, some study might find that drinking…

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