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W05: Evidence and uncertainty: a modeling and simulation-based approach to statistical inference


With Andrew Zieffler & Michael Huberty (University of Minnesota), Jason Dolor, Kit Clement, & Jennifer Noll (Portland State University)


Schedule

Wednesday May 15, 1:00 pm – 4:30 pm
Thursday May 16, 8:30 am – 12:00 pm

Abstract

This workshop will introduce a modeling and simulation approach to teaching statistical inference which can deepen students’ understanding of the inferential process and enable them to investigate more complex phenomena. We will cover how to use TinkerPlots (a dynamic exploration and modeling tool) to create simple and complex probability models in order to help students understand sampling variability. We will then use these models as a catalyst for understanding and carrying out statistical inference via randomization and bootstrap methods. Throughout the workshop, participants will be exposed to interactive hands-on activities that they can then implement into their classrooms. In addition, we will also introduce participants to how they can use a student-centered, group-based pedagogical approach to teaching statistics. These activities are used in a one term introductory college statistics courses, but are also appropriate for secondary school curriculum.


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