Rob Kass is Maurice Falk Professor of Statistics and Computational Neuroscience at Carnegie Mellon University, where he served as Department Head of Statistics for nine years. His many research interests have focused on Bayesian inference and applications of statistics to neuroscience. He is a Fellow of the American Statistical Association, the Institute of Mathematical Statistics, and the American Association for the Advancement of Science. He has written about statistics education in such articles as "What is Statistics?" (with Emery Brown, The American Statistician) , "Statistical Inference: The Big Picture" (Statistical Science), and "Ten Simple Rules for Effective Statistical Practice" (with others, PLOS Computational Biology).
Deb Nolan is Professor of Statistics at the University of California, Berkeley, where she holds the Zaffaroni Family Chair in Undergraduate Education. She has also served as Chair of the Statistics Department and Associate Dean of Mathematical and Physical Sciences. She is a Fellow of the American Statistical Association and the Institute of Mathematical Statistics. Her contributions to statistics education include the books StatLabs: Mathematical Statistics through Applications (with Terry Speed), Teaching Statistics: A Bag of Tricks (with Andrew Gelman), Data Science in R: A Case Studies Approach to Computational Reasoning and Problem Solving (with Duncan Temple Lang), and XML and Web Technologies for Data Sciences with R (also with Duncan Temple Lang).
Mine Çetinkaya-Rundel is an Associate Professor of the Practice in the Department of Statistical Science at Duke University and a Professional Educator at RStudio. She received her Ph.D. in Statistics from the University of California, Los Angeles. Çetinkaya-Rundel’s work focuses on innovation in statistics pedagogy, with an emphasis on student-centered learning, computation, reproducible research, and open-source education. She teaches the popular MOOC titled Statistics with R on Coursera. She is a co-author of three open-source statistics textbooks as part of the OpenIntro project as well as a co-editor of and regular contributor to the Citizen Statistician blog and Taking a Chance in the Classroom column in Chance Magazine.
Jay Lehmann is Professor of Mathematics at the College of San Mateo, where he has taught for the past 22 years and received the “shiny apple award” for excellence in teaching. He has presented talks on pre-statistics, curve fitting in algebra courses, and directed-discovery learning at over 80 conferences over the past fifteen years. He has participated in grant projects on retooling an arithmetic course and on learning how to assess the effectiveness of teaching. He has authored several algebra textbooks and has just completed a pre-statistics textbook.