Statistical Thinking: A Simulation Approach to Modeling Uncertainty (UM Spring 2023 edition)
Statistical Thinking: A Simulation Approach to Modeling Uncertainty (STAT 216 edition)
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 Thinking: A simulation approach to uncertainty (University of Montana, Spring 2023 ed.). https://bookdown.org/frederick_peck/statistical_thinking_um_spring_2023_ed/
The work to create the material appearing in the book was made possible by the National Science Foundation (DUE–0814433).
This book is a modified version of the work 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
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).
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