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Roundtable on Data Science Postsecondary Education Meeting: Reproducibility and Teaching Data Science as a Scientific Process

  • University of California, Berkeley Institute for Data Science 190 Doe Library Berkeley, CA 94704 (map)

Buried in Data, Starving for Information: How measurement noise is blocking scientific progress.

Timothy S. Gardner, Founder/CEO

Today's breakthroughs lie deep in the midst of complex, multivariate data sets. Yet, experimental anomalies and fundamental discoveries often go unnoticed because they are buried in uninterpretable spreadsheets, inaccessible databases, or excessive experimental noise. Moreover, our educational system is failing to train our scientists in fundamental principles of experimental design, measurement systems analysis, and quality. The result is missed opportunities for scientific discovery, lost time chasing experimental artifacts, and stunted learning cycles. We will illustrate these issues with examples from present day research, and outline solutions to these problems derived from 100 years of statistical science and manufacturing quality principles.