This paper is from Session 3B: Randomisation and bootstrapping: the quick way to inference
which comes under Topic 3: Statistics education at the post-secondary level
Paper 3B3 (Monday 9th, 16:00-17:30)
Connecting Intuitive Simulation-Based Inference to Traditional Methods
Presenter
- Robin Lock (St. Lawrence University, United States)
Co-author
- Patti Frazer Lock (St. Lawrence University, United States)
Abstract
Simulation-based methods have become increasingly popular as a way to introduce students to the core ideas of statistical inference. Yet most advocates of this approach still recognize the need for students to also be exposed to traditional, formula-based methods based on normal and t-distributions. As we have gained experience with building basic intuitions for inference through simulations, we have also refined methods to extend those ideas to make the connections to learning traditional methods easier and more efficient. We explore how these methods help students translate the “big picture” ideas of simulation, that apply to many parameter situations, to see the common structures of traditional methods.