Publications

For a complete, up-to-date list, see my Google Scholar profile.

Selected Publications

  1. N Taback. Generative AI Spotlights the Human Core of Data Science: Implications for Education. arXiv preprint, 2026.
  2. JY Oh, MJ Moon, M Liut, M Choi, K Huynh-Wong, N Taback. A Randomized Study Comparing the Effectiveness of an Untrained Versus Trained Chatbot—With Access to Course Content—in an Introductory Mathematical Statistics Course. ICOTS-12 Conference Proceedings, 2025.
  3. JC He, GT Moffat, S Podolsky, F Khan, N Liu, N Taback, S Gallinger, et al. Machine learning to allocate palliative care consultations during cancer treatment. Journal of Clinical Oncology, 2024.
  4. C Fernandes, JD Vescovi, R Norman, CL Bradish, N Taback, TCY Chan. Equity, diversity, and inclusion in sports analytics. Journal of Quantitative Analysis in Sports, 2024.
  5. A Sarma, A Kale, MJ Moon, N Taback, F Chevalier, J Hullman, M Kay. multiverse: Multiplexing alternative data analyses in R notebooks. Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 2023. Honorable Mention.
  6. N Taback, AL Gibbs. A Randomized Study to Evaluate the Effect of a Nudge via Weekly E-mails on Students’ Attitudes Toward Statistics. Journal of Statistics and Data Science Education, 2023.
  7. N Taback. Design and Analysis of Experiments and Observational Studies using R. Chapman and Hall/CRC, 2022.
  8. AL Gibbs, N Taback. The Building Blocks of Statistical Education in the Data Science Ecosystem. Harvard Data Science Review, 2021.
  9. N Taback. Do you have experience? Incorporating experiential learning opportunities into statistics education is messy but important. Proceedings of the 10th International Conference on Teaching Statistics (ICOTS10), 2018.
  10. N Taback. The Dirty War Index: statistical issues, feasibility, and interpretation. PLoS Medicine, 2008.

Software