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2008 was a historic year in many ways, perhaps the most prominent being the election of the first African American president. But 2008 also saw an unlikely hero emerge amongst the record setting presidential race... Nate Silver and his astonishingly accurate prediction of its results. More important than Nate's remarkable result however was the attention it drew to the potential of data and the importance of uncertainty (through bayesian statistics). And it was in that moment that our modern incarnation of data journalism was born (though ironically the field dates back to an attempt to predict the 1952 presidential election) with Nate's (now famous) 538 blog.
In this talk I will walk through the approach that made Nate so successful in 2008, test its efficacy in predicting the early 2016 primary results, and show how these (relatively) simple concepts can be applied in novel ways to tangential fields to great effect (for fun and profit) by estimating the time to failure for industrial machines in our connected world of the IoT.