Image Credit: A flickr photo by Robert Occhialini


Change Agents for Teaching and Learning Statistics (CATALST) was an NSF-funded project that developed materials for teaching a radically different introductory statistics course based on randomization and bootstrap methods to provide students a deep understanding of statistical inference.

The materials were turned into a free, online book, Statistical Thinking: A Simulation Approach to Modeling Uncertainty, available at:

The data sets and PDF version of the lab manual are available at the book’s Github repository:


(2015). Assessing Learning Outcomes: An Analysis of the GOALS-2 Instrument. Statistics Education Research Journal, 14(2), 93–116.

PDF Project

(2015). A Catalyst for Change in the High School Math Curriculum. CHANCE, 28(3), 44–49.


(2014). Developing Students' Reasoning about Samples and Sampling Variability as a Path to Expert Statistical Thinking. Educational Studies in Mathematics, 88(3), 327–342.

Project Source Document

(2013). The Course as Textbook: A Symbiotic Relationship in the Introductory Statistics Class. Technology Innovations in Statistics Education, 7(3).

PDF Project

(2012). Developing Statistical Modelers and Thinkers in an Introductory, Tertiary-Level Statistics Course. ZDM—The International Journal on Mathematics Education, 44(4), 883–898.