Mine Çetinkaya-Rundel receives Robert V. Hogg Award for Excellence in Teaching Introductory Statistics

Mine Çetinkaya-Rundel

Mine Çetinkaya-Rundel receives Robert V. Hogg Award for Excellence in Teaching Introductory Statistics

(The following is a slightly edited version of a story about the award that will appear in the Mathematical Association of America Focus news magazine.) 

Dr. Mine Çetinkaya-Rundel is the 2021 recipient of the Robert V. Hogg Award for Excellence in Teaching Introductory Statistics.  The Robert V. Hogg award for Excellence in Teaching Introductory Statistics is named in honor of Robert V. Hogg, who was a passionate advocate for statistics education, a winner of numerous teaching accolades including the Iowa Governor’s Science Medal for Teaching in 1990 as well as MAA’s Distinguished Teaching award in 1993, and served as the President of the American Statistical Association in 1988.

Dr. Çetinkaya-Rundel is an Associate Professor of the Practice at Duke University and currently Senior Lecturer at the University of Edinburgh, as well as Data Scientist and Professional Educator at RStudio. She is a Fellow of the American Statistical Association as well as an International Statistical Institute Elected Member, as well as a recipient of the 2016 Waller Education Award of the American Statistical Association.

At Duke and the University of Edinburgh, she has focused on developing student-centered classes that rely on team-based and flipped-classroom approaches. Even in introductory courses with no prerequisites, she teaches students to “think with data,” integrating the use of R Markdown and reproducible research practices throughout. In 2019 she created a new introductory data science course that is so popular that the number of sections has since doubled. Her teaching of introductory statistics and data science also includes several MOOC courses available through Coursera as well as education offered through RStudio.

Beyond her own teaching, her influence stretches extensively to introductory statistics and data science students at other universities as well. She has been instrumental in the creation of the widely-used OpenIntro series of open-source statistics textbooks and materials. Most recently in this series, she has been developing, with Jo Hardin, the new textbook “Introduction to Modern Statistics” which is an update and expansion of the OpenIntro book utilizing simulation-based inference approaches. Further, she has worked to extend the outreach of the ASA DataFest event across the country, giving undergraduate students the experience of analyzing real, complex datasets in a weekend event.

Her influence also extends to the training and support of other introductory statistics and data science educators. She has led USCOTS workshops teaching the reproducible research framework, and also is co-coordinator of the CHANCE magazine “Taking a Chance in the Classroom” column, which offers innovative ways to improve the introductory statistics classroom. Further, she has developed Data Science in a Box, an open-source repository for educational materials to be used in introductory data science courses.