Health Data Science Distinguished Speaker: Roger Peng, PhD, University of Texas, Austin
Date: Sept 21, 2023
Location: BMC Hiebert Lounge, 72 E. Concord St, 14th Floor, Boston, or Zoom
Talk Title: Principles for Designing Complex Data Analyses
Abstract: Data analyses have grown more complex over time in part due to tremendous advances in data collec-tion, measurement technologu, and computational power. These advances have allowed us to measure the world in ever greater detail and apply complex models from which we can learn about the underlying phenomena being studied. However, the unrestricted and undisciplined analuses of complex datasets has led to a proliferation of non-repro-ducible findings. As the data science revolution continues forward and touches all areas of society, we propose that there is a need to specify the craft of data analysis in more formal terms. Some benefits of formalizing the data analysis process include the development of novel metrics of data analysis quality, the articulation of principles for analytic design, and the ability to scale the teaching of data analysis to large audiences. We will present a theoretical framework for the analutic process and describe its potential for improving the quality of data analysis.
Bio: Roger D. Peng is a Professor of Statistics and Data Sciences at the University of Texas, Austin. Previously, he was Professor of Biostatistics at the Johns Hopkins Bloomberg School of Public Health and the Co-Director of the Johns Hopkins Data Science Lab. His current research focuses on developing theory and methods for building successful data analyses and on the development of statistical methods for addressing environmental health problems. He is the author of the popular book R Programming for Data Science and 10 other books on data science and statistics. He is also the co-creator of the Simply Statistics blog where he writes about statistics for the public, the Not So Standard Deviations podcast with Hilary Parker, and The Effort Report podcast with Elizabeth Matsui. Roger is a Fellow of the American Statistical Association and is the recipient of the Mortimer Spiegelman Award from the American Public Health Association, which honors a statistician who has made outstanding contributions to public health.
Co-sponsors: The SPH Population Health Data Science Program, the Hariri Institute for Computing and Computational Science & Engineering, the SPH Department of Biostatistics, and the Providence/Boston Center for AIDS Research (CFAR)