Selected Publications


Justice, N., Zieffler, A., Huberty, M., & delMas, R. (2018). Every rose has it's thorn: Secondary teachers' reasoning about statistical models. ZDM—The International Journal on Mathematics Education, 50(7), 1253–1265. doi: 10.1007/s11858-018-0953-1

National Academies of Sciences, Engineering, and Medicine. (2018). [Contributing Author]. Data science for undergraduates: Opportunities and options. Washington, DC: The National Academies Press. doi: 10.17226/25104

Sabbag, A. G., Garfield, J., & Zieffler, A. (2018). Assessing statistical literacy and statistical reason- ing: The REALI instrument. Statistics Education Research Journal, 17(2), 141–160.


Garfield, J., Zieffler, A., & Fry, E. (2017). What is statistics education? In D. Ben-Zvi, K. Makar, & J. Garfield (Eds.), The international handbook of research in statistics education (pp. 37–70). Cham, Switzerland: Springer International Publishing.

Stanhope, E., Ziegler, L., Haque, T., Le, L., Vinces, M., Davis, G. K., Zieffler, A., Brodfuehrer, P., Preest, M., Belitsky, J., Umbanhowar, Jr., C., & Overvoorde, P. J. (2017). Development of a Biological Science Quantitative Reasoning Exam (BioSQuaRE). CBE–Life Sciences Education, 16(4), ar66. doi: 10.1187/cbe.16-10-0301

Justice, N., Zieffler, A., & Garfield, J. (2017). Statistics graduate teaching assistants’ beliefs, practices, and preparation for teaching introductory statistics. Statistics Education Research Journal, 16(1), 294–319.


Sabbag, A. G., & Zieffler, A. (2015). Assessing learning outcomes: An analysis of the GOALS-2 instrument. Statistics Education Research Journal, 14(2), 93–116.

Zieffler, A., & Fry, E. (eds.) (2015). Reasoning about uncertainty: Learning and teaching informal inferential reasoning. Minneapolis, MN: Catalyst Press.

Zieffler, A., & Huberty, M. (2015). A catalyst for change in the high school math curriculum. CHANCE, 28(3), 44–49. doi: 10.1080/09332480.2015.1099365

Umbanhowar Jr., C, Belitsky, J. M., Brodfuehrer, P., Davis, G., Haque, T., Le, L., McFadden, C., Overvoorde, P., Preest, M., Stanhope, L., Vinces, M., Zieffler, A., & Ziegler, L. (2015). Understanding the quantitative and computational skills of incoming biology students.

Recent Blog Posts

Minnesota State High School Boys Hockey Predictions (Updated Quarterfinals)

In a previous post, I used Monte Carlo simulation to predict the winner of the 2018 Minnesota State High School Boys Hockey tournament. Now that the quarterfinal games have been played, I thought I would update my predictions. The process for this is to: Update the Elo ratings based on the quarterfinal games; Re-simulate the tournament I simulated the Class A state tournament 10,000 times using the same process as described in my previous post.

Minnesota State High School Boys Hockey Predictions

The state high school boys hockey tournament, scheduled for March 7–10, is one of the premiere sporting events in the state of Minnesota. According to Wikipedia, this event has drawn over 100,000 spectators 22 times in its history, eclipsing 135,000 spectoators in 2015. Many national caliber players played high school hockey in Minnesota, several taking part in the state tournament. Names like Neal Broten, Herb Brooks, and T. J. Oshie are alumni of state tournaments past.

College in the Schools

College in the Schools is a concurrent enrollment program in which existing University of Minnesota courses are taught in high schools by high school teachers. All schools wishing to offer a CIS course go through an application process, including an interview and approval by the post-secondary academic department sponsoring the course of any high school teachers who will be teaching the course. Since CIS is a concurrent enrollment program, students are enrolled simultaneously in the University of Minnesota course (EPsy 3264: Basic and Applied Statistics) and a course at their high school.

EPsy 3264: Basic and Applied Statistics

EPsy 3264 is a 3-credit course designed to engage students using a modeling and simulation approach to inference. This course fulfills the Mathematical Thinking component of the Liberal Education requirements at the University of Minnesota. Statistics is more than just an application of mathematics or a methodology used in some other discipline. Statistics is a principled way of thinking about the world. In particular, it is a principled approach to data collection, prediction, and scientific inference.