Jeff is a professor of Biostatistics and Oncology at the Johns Hopkins Bloomberg School of Public Health. His research focuses on public health genomics, data science as a science, and research on the scientific literature. He is also co-creator of the Johns Hopkins Data Science Specialization on Coursera (https://www.coursera.org/specializations/jhu-data-science) that has enrolled over 4 million. He is a co-editor of the journal Biostatistics. He writes a blog at Simply Statistics and is the author of the best-selling book "The Elements of Data Analytic Style" (https://leanpub.com/datastyle/).
Data science is as much an art as it is a science. Human intuition, judgement, and choices play a critical role in the answers we get from any data analysis. In this talk I will discuss the work of our group in studying human data interaction, including the tidycode package for analyzing R code, and experiments we are running in our massive online open courses to study the decision making behind data analysis.