First and foremost, I am an who is educator passionate about meeting learners where they are and understanding how they learn so that I can build better resources, pedagogy, and tooling to support their learning. My main teaching and research interest is statistics and data science education, particularly using R. I have been at Duke University since 2011 and I had a brief stint at the University of Edinburgh in 2019-2021. Prior to Duke, I received my PhD in Statistics at UCLA in 2011, under the advisement of Jan de Leeuw, and my BS in Actuarial Science at NYU’s Stern School of Business in 2004. In between undergraduate and graduate degrees, I worked as a consulting actuary for two years in New York.
Statistical Science at Duke
You can find out everything you need to know about majoring in Statistical Science at Duke here. If you would like to meet to discuss degree options in the department, you can book a time to meet with me here or send an email to firstname.lastname@example.org.
Statistics and data science education
I primarily work on developing open-educational resources and software for modern statistics and data science education as well as pedagogies for enhancing the student experience in data science and statistics courses. I also work on research projects that aim to assess the effectiveness of these approaches with respect to learning and retention. My computing language of choice is R, though I’m always interested in learning about how educators teaching different languages approach the same challenges. At any given point I have numerous projects active in this area. If you’re a student wanting to work with me or a potential collaborator, I’d love to hear from you.
Open educational resources
I believe in building open-source, open-access resources for education. I have co-authored four open-source statistics textbooks as part of the OpenIntro project at the introductory college and advanced high school level. I am also the creator and maintainer of Data Science in a Box and I have been developing and teaching various massive open online courses, including the popular Statistics with R specialization on Coursera. Materials for all courses and workshop I’ve taught are also openly licensed. You can find them on my teaching page.
I co-lead the international effort for putting on ASA DataFest, a two-day competition in which teams of undergraduate students work to reveal insights into a rich and complex data set, annually at over fifty institutions across the globe.
Consulting and training
I enjoy working with research and industry teams on solving challenges (particularly those related to R) and providing training. Previous talks and workshops I’ve delivered can be found here and here, respectively. If you’re interested in setting up a consulting or a training session with me, send me an email here.
Honors and Awards
- The Robert V. Hogg Award For Excellence in Teaching Introductory Statistics, 2021.
- Young Academy of Scotland Elected Member, 2020.
- Teacher of the Year Nominee. University of Edinburgh, 2020.
- American Statistical Association Fellow, 2019.
- International Statistical Institute Elected Membership, 2019.
- Harvard Pickard Award, 2018.
- ASA Waller Education Award, 2016.
- Best Paper Award JSM 2015 Section on Teaching Statistics in the Health Sciences.
- David and Janet Vaughan Brooks Award for Teaching Excellence. Duke University, 2014.
How can we effectively and efficiently teach data science to students with little to no background in computing and statistical thinking? How can we equip them with the skills and tools for reasoning with various types of data and leave them wanting to learn more? This introductory data science course is our (working) answer to this question.Read more
OpenIntro’s mission is to make educational products that are free, transparent, and lower barriers to education. We also feature supporting resources, such as slides, videos, and more.Read more