DATA SOURCES and STATISTICAL ISSUES Form

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Hi, I’m Adriene Hill, and welcome back to Crash Course Statistics. In the last episode, we talked about the value of Big Data. But, as Big Data (and the statistics we do with it) permeate more areas of our lives, there are also new problems that come up. How can we learn from useful data while still keeping it safe and private? When there’s SO much data that we have to rely on algorithms to manage it can we trust those algorithms? Today, we’re going to have a discussion about the potential downsides of Big Data in our lives and some possible solutions. INTRO Let’s start with a Thought Bubble. This story comes out of a collaboration between the University of Washington and the University of California Irvine. The team wanted to create an algorithm that could take an image and determine whether it was of a husky or a wolf. To do that, they trained the algorithm with a bunch of pictures. These images are a great example of “BIG DATA” that we CAN wrap our heads around. Pictures