by Angela Guess
George Mount recently wrote in Smart Data Collective, “This week I read a great piece by Adam Weinberg, the president of Denison University, on his school’s initiatives to apply a liberal arts approach to data science. This is shocking to most, but why? Let’s diagram this phrase ‘data science’ (English skills!). Data is information — let’s leave it at that for now. But what about science? Science is the testing of observable phenomena. It is built on the scientific method of observing, making hypotheses, and testing them. So the ‘data mining’ approach of pointing out quirky relationships in data with no guiding theory is one thing. ‘Data science’ is another. Because as a science, it must be grounded in the scientific method.”
Mount goes on, “And science has long been a part of any liberal arts education. I took two in college — they were some of my easier classes, but I still took them. In fact, I was required to take them to graduate. In the meantime, I also took classes in literature and history. I learned what’s worked and what hasn’t in human history through studying the great books. I learned how to write and communicate. And in my science classes, I learned how to make hypotheses from these observations, and test them. An economics major, I was able to examine what worked and hasn’t in terms of human flourishing, for example. This can’t be said about many pre-professional or even many STEM programs — they’re more concerned with passing off knowledge to you and not showing you how to test and generate ideas of your own.”
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