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Activity Number: 152 - Making an Impact in Statistics Education: Waller Award Winner Perspectives
Type: Invited
Date/Time: Monday, July 29, 2019 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics and Data Science Education
Abstract #300436 Presentation
Title: Teaching with Simulation-Based Inference Methods in 2020 and Beyond
Author(s): Nathan Tintle*
Companies: Dordt College
Keywords: p-value; multivariable; data science; simulation; introductory statistics; teaching

Evidence continues to indicate that simulation-based inference (SBI) is contributing to improved student learning outcomes in introductory statistics courses. I’ll discuss emerging evidence for best practices in teaching with SBI and the use of SBI in multivariable contexts. These comments come in light of assessment data from thousands of students and the experiences of hundreds of faculty using these methods. I’ll also discuss the role of SBI methods in the context of contemporary movements like data science and ongoing questions about the use of p-values in scientific practice. Finally, I’ll highlight open questions about teaching with simulation-based inference methods that will need to be investigated in the years to come.

Authors who are presenting talks have a * after their name.

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