Statistical Reasoning:
A Modeling and Simulation Approach

This is a free, activity-based introductory statistics class, suitable for high-school and college students. The course is designed around active learning, statistical modeling, and computational thinking. Students use Monte Carlo Simulation to model variability, and they make conclusions based on the outcomes of their models. This process is sometimes known as simulation-based inference.

There are two primary materials: the online textbook and a set of 47 class activities in Desmos.

Licensing and Attribution

This work is licensed under a Creative Commons Attribution 4.0 International License. You are free to share, remix, and make commercial use of the work under the condition that you provide proper attribution. To reference this work, use:

Peck, F.A., Zieffler, A., & Catalysts for Change. (2023). Statistical Reasoning: A modeling and simulation approach. https://www.fapeck.com/statistical-reasoning 

This course is based on the work of the Catalysts for Change project at the University of Minnesota.  

The text and activities are direct descendants of the curriculum below: 

Zieffler, A., & Catalysts for Change. (2019). Statistical Thinking: A simulation approach to uncertainty (4.2th ed.). Minneapolis, MN: Catalyst Press. http://zief0002.github.io/statistical-thinking/ 

The original curriculum is a direct reflection of the ideas, work, and effort of several Catalysts for Change. They include (alphabetically): Ethan Brown, Jonathan Brown, Dan Butler, Tony Casci, Beth Chance, George Cobb, Robert delMas, Katherine Edwards, Michelle Everson, Jeffrey Finholm, Chris Fiscus, Elizabeth Fry, Joan Garfield, Theresa Gieschen, Meg Goerdt, Robert Gould, Adam Gust, Melissa Hanson, John Holcomb, Michael Huberty, Rebekah Isaak, Kari Johnson, Nicola Justice, Laura Le, Chelsey Legacy, Suzanne Loch, Matthew Mullenbach, Michael Nguyen, Amy Okan, Allan Rossman, Anelise Sabbag, Andrew Zieffler, and Laura Ziegler. The work to create the original curriculum was made possible by the National Science Foundation (DUE–0814433).

Additionally, some of the activities were originally developed by Beth Chance, George Cobb, John Holcomb, and Allan Rossman as part of their NSF-funded project Concepts of Statistical Inference: A Randomization-Based Curriculum (NSF CCLI- DUE-0633349).