Data Can Lie–Here's A Guide To Calling Out B.S.

According to the University of Washington professors Carl T. Bergstrom and Jevin West, it's time someone did something about it. It's a free structured course of readings and case studies aimed at giving students (and anyone who might be interested) the tools to look critically at scientific claims driven by data and machine learning. Over the past six months, the two scientists created the syllabus and published it online in the hopes that the UW administration would take notice and turn it into a real class (it's currently winding its way through the approval process, and might be offered as soon as the spring). The two have been frustrated with the way statistical findings are treated in the media and in the classroom for years. West, a professor in the Information School and the director of UW's Data Lab, believes that thanks to the emergence of big data and the increasing availability of tools that help more people work with it, the amount of bullshit appears to have increased; with so much data out there, there is simply more potential for data scientists and designers to shape it to fit their own conclusions–or even intentionally mislead their audience.