10th International
Conference on
Teaching Statistics
8 – 13 July 2018
Kyoto, Japan
Full topic list
This is a session of Topic 3: Statistics education at the post-secondary level


Session 3B (Monday 9th, 16:00-17:30,   Terrsa Hall)

Randomisation and bootstrapping: the quick way to inference


Organizer


Abstract

In introductory statistics courses, we establish the connected ideas of sampling variation and randomisation of group labels early on and then embark on a long and convoluted road to classical statistical inference. In navigating our way along this path, we often confuse and even lose many of our students due to the multitude of ideas and concepts we have to teach them. We need to be able to establish the core concepts of statistical inference much faster and connect better with their prior experience and intuition, not only to maintain our students’ interest but also to prepare them for when we do move to the more formal ideas of mathematically based inference. If we can establish the core concepts of inference early on, our students will have a much better idea of where they are going and why they need to go there. Modern computer technology now allows us to use interactive visualisations of statistical techniques such as bootstrapping and randomisation tests so that we can have beginners doing statistical inference in a matter of hours rather than days or weeks. Since the session at ICOTS9, what has been discovered, adjusted and learnt about this new way of teaching inference?


Papers

PaperTitlePresenter / Co-author(s)
3B1Development of a tool to assess students’ conceptual understanding in introductory statisticsNathan Tintle (United States)
Jill VanderStoep (United States)
3B2Student Gains in Conceptual Understanding in Introductory Statistics With and Without a Curriculum Focused on Simulation-Based InferenceBeth Chance (United States)
Nathan Tintle (United States)
Stephanie Mendoza (United States)
3B3Connecting Intuitive Simulation-Based Inference to Traditional MethodsRobin Lock (United States)
Patti Frazer Lock (United States)