Abstract:
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How does any statistician or analyst—whether in academia, industry, or government—get involved in data science? How do we prepare ourselves or our colleagues to answer new questions, update old explanations in light of new knowledge, or even determine if the new tools of data science are suitable for our usual questions? A panel consisting of three statisticians and an economist will discuss strategies for upskilling a statistician with the knowledge and tools needed to be relevant in the field of data science. The panel will be of particular interest to classically trained statisticians who want to add data science to their portfolio but do not know where to begin. Panelists will address how statistics and data science differ, common data science tools, potential academic routes for retraining a statistician to become a data scientist, paths for introducing data science into a statistics department or degree program, the differences between data science courses and statistics courses, strategies for bringing in other disciplines, and the costs and benefits of retraining.
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