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Thursday, June 30 • 9:00am - 10:00am
Statistical Thinking in a Data Science Course

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The intuition and experience needed for sound statistics practice can be hard to learn, and a course that combines computing, statistics, and working with data offers an excellent learning environment in this regard. Moreover, an integrated approach to data science creates opportunities to reinforce statistical thinking skills throughout the full data analysis cycle, from data acquisition and cleaning to data organization and analysis to communicating results. As a result, students gain the ability to reason computationally, actively engage in statistical problem solving, and learn how to keep abreast of new technologies as they evolve. This talk describes approaches and provides examples for teaching data science in this integrated fashion.

avatar for John Chambers

John Chambers

Stanford University

avatar for Deborah Nolan

Deborah Nolan

Professor, UC Berkeley

Thursday June 30, 2016 9:00am - 10:00am PDT
McCaw Hall